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Array Design and Robust Array Signal Processing: Advancements, Insights and Applications

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Submission Deadline: 31 December 2020

Most of the array processing approaches have been developed under the assumption of ideal conditions as follows:

Identical channel gain (amplitude and phase) of antenna array. Perturbation effects or mutual coupling of sensor array are common in real engineering applications, and so robust array calibration for parameter estimation or beamforming is required in array signal processing.

Additive white Gaussian noise (WGN) environments. In real scenarios, many observed processes have been found to be non-Gaussian or colored, such as the lightning in the atmosphere, the influence of mountains and sea waves, the switching transients in power lines and the underwater acoustic signals. These non-Gaussian signals and colored noises would cause significant degradation in system performance if optimized under the assumption that they are white Gaussian distributed.

On the other hand, due to application requirements related to antenna array systems, such as MIMO radar, massive MIMO and millimeter-wave communication for the 5th generation wireless systems, the special array design or configuration for various sensor arrays has drawn more attention in the past decade. Sparse array, nested array and co-prime array provide a systematic framework for sparse sampling and array configuration with increased degrees-of-freedom. In addition, asymmetrically shaped beam patterns could be synthesized to estimate Direction-of-Arrival (DOA) or track spatially mobile sources.

This special section aims to advance knowledge by antenna array designers and signal processing practitioners. It will include recent research advancements in and applications of array design and robust array signal processing under non-ideal conditions. For real applications, new array design approaches are needed, and robust statistical methods are investigated in order to account for the fact that the postulated models for the data are fulfilled only approximately and not exactly. Novel research results will be presented, offering innovative contributions either from a methodological or an application point of view. Review articles on this topic are also welcome.

Potential topics include but are not limited to the following:

• Sparse, nested array and coprime array design
• Array beam pattern synthesis for particular application
• Antenna array calibration
• Sparse signal reconstruction in array signal processing
• Parameter estimation in non-ideal conditions (i.e. colored noise, non-stationary)
• Robust beamforming with erroneous sensors
• Co-prime/random array signal processing
• DOA estimation in non-line-of-sight environments in wireless sensor networks
• Advanced array processing methods for applications including MIMO radar, radio astronomy, sonar, speaker localization, and wireless communications
• Various array design
• Array calibration
• Robust array signal processing
• DOA estimation
• Adaptive beamforming

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Electrical Engineering and Systems Science > Signal Processing

Title: three more decades in array signal processing research: an optimization and structure exploitation perspective.

Abstract: The signal processing community currently witnesses the emergence of sensor array processing and Direction-of-Arrival (DoA) estimation in various modern applications, such as automotive radar, mobile user and millimeter wave indoor localization, drone surveillance, as well as in new paradigms, such as joint sensing and communication in future wireless systems. This trend is further enhanced by technology leaps and availability of powerful and affordable multi-antenna hardware platforms. The history of advances in super resolution DoA estimation techniques is long, starting from the early parametric multi-source methods such as the computationally expensive maximum likelihood (ML) techniques to the early subspace-based techniques such as Pisarenko and MUSIC. Inspired by the seminal review paper Two Decades of Array Signal Processing Research: The Parametric Approach by Krim and Viberg published in the IEEE Signal Processing Magazine, we are looking back at another three decades in Array Signal Processing Research under the classical narrowband array processing model based on second order statistics. We revisit major trends in the field and retell the story of array signal processing from a modern optimization and structure exploitation perspective. In our overview, through prominent examples, we illustrate how different DoA estimation methods can be cast as optimization problems with side constraints originating from prior knowledge regarding the structure of the measurement system. Due to space limitations, our review of the DoA estimation research in the past three decades is by no means complete. For didactic reasons, we mainly focus on developments in the field that easily relate the traditional multi-source estimation criteria and choose simple illustrative examples.

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• Published: 28 October 2021

Design and SAR assessment of three compact 5G antenna arrays

• Z. Adelpour 1 ,
• H. Oraizi 2 &
• N. Parhizgar 1  

Scientific Reports volume  11 , Article number:  21265 ( 2021 ) Cite this article

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In this paper three different multi stub antenna arrays at 27–29.5 GHz are designed. The proposed antenna arrays consist of eight single elements. The structure of feeding parts is the same but the radiation elements are different. The feeding network for array is an eight way Wilkinson power divider (WPD). To guarantee the simulation results, one of the proposed structures is fabricated and measured (namely the characteristics of S 11 , E-, and H-plane patterns) which shows acceptable consistency with measurement results. The simulation results by CST and HFSS show reasonable agreement for reflection coefficient and radiation patterns in the E- and H- planes. The overall size of the proposed antenna in maximum case is 29.5 mm × 52 mm ×  0.38 mm  (2.8 \({{\varvec{\lambda}}}_{0}\) × 4.86 \({{\varvec{\lambda}}}_{0}\) × 0.036 \({{\varvec{\lambda}}}_{0}\) ). Moreover, for Specific Absorption Rate (SAR) estimation, a three-layer spherical human head model (skin, skull, and the brain) is placed next to the arrays as the exposure source. The simulation results show that the performance of proposed antennas as low-SAR sources makes them ideal candidates for the safe usage and lack of impact of millimeter waves (mmW) on the human health. In all three cases of SAR simulations the value of SAR 1g and SAR 10g are below the standard limitations.

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Introduction.

Recently the 5G technology has become an attractive subject in the telecommunication industry. Upcoming 5G systems should satisfy several requirements such as: higher bandwidth, low latency, broad coverage of network, high reliability, high throughput, high connection density, low power consumption, high gain 1 . Some frequency bands have been proposed as candidates for millimeter wave (mmW) for example 27–29.5 GHz, 36–40 GHz, 47.2–50.2 GHz 2 . High path loss owing to reduced size of antenna dimenssions and increasing atmospheric absorption are two problems at high frequency. Although higher data rates can support by these frequency bands but the signal wavelength becomes shorter and according to the Friis equation, the free space path loss becomes higher 3 , 4 . Imployment of high gain directive antennas or antenna array is a solution to compensate such problems, which provides multipath supperssion and interference mitigation however low radiation toward human tissues is expected to achive low specific absorption rate 5 .

The 5G antennas usually use in handheld devices, such as tablets and mobile phone therefore they evidently should be small in size and light weight. It has been demonstrated when the radiation patterrn of antenna is directed to the top or bottom edges of the devices (that is endfire pattern) the influence of user’s hand on the antenna radiation is minimize 6 . Antenna arrays at 5G systems can be designed by some technologies such as microstrip and SIW 7 , 8 , and in many types like fermi, vivaldi, quasi yagi, and cavity backed 9 , 10 , 11 . However, the effects of electromagnetic field on human body tissue should evaluate by possible methods like numerical methods to ensure that these field sources do not threaten human health at 5G frequency bands. To appraise the exposure some parameters use by standard institutes such as Specific Absorption Rate (SAR), power density (PD), and the Skin Surface Temperature Elevation. There are some standards, such as Federal Communications Commission (FCC) and IEEE to determine the permissable values of SAR from exposure to electromagnetic fields for human safety. Their values are different for occupational and public environments. According to these standards the SAR 1g and SAR 10g limits are 1.6 W/kg and 2 W/kg repectively 12 .

The studies about SAR levels on human tissues have been done in many vaious conditions and methods such as in vivo–in vitro environment and also by numerical methods. Duo to the probable hazards on human health in actual conditions, many assesments about field exposure are conducted by software simulations and exprimental environments. In 13 , for the determination of SAR, the human body tissues are modeled in one (skin) and three layer (including skin, fat, and muscle) and a four-element array of rectangular patch antenna as an exposure source have been modeled by the CST softawre. The input powers were 20 dBm and 24 dBm and the frequencies were 28, 40 and 60 GHz. The results showed that at both power, SAR 1g and point SAR values at 28 GHz were lower than other frequencies 14 , the penertation of radiation at 30 GHz in human ear canal and tympanic membrane have been investigated and the results showed a very low penetration and not notable significant thermal effect on the tympanic membrane. In 15 the absorption of RF field at 39 GHz both in invivo bovine the brain tissue and a brain simulating gel model have been investigated. The results represented the SAR and radiation penetration in the brain model, and therefor SAR, decreases with increasing depth and frequency. In 16 the SAR values in head model of children and adults at 28 GHz (30 mW) and a microstrip antenna as a field source have been simulated. The results showed that absorption in tissues decreasing rapidly in depth. As well as duo to epidermis and dermis thickness (0.1 and 2 mm), the mmW values values are quickly absorbed in these layers and do not reach the deeper tissues.In this paper three compact, lightweight, high gain eight arrays antenna are simulated at 27–29.5 GHz. Design procedure, simulation, and measurement results are presented in the following sections. Also the SAR 1g and SAR 10g have been simulated and evaluated to determine the specific absorption rate.

Antenna design

Feeding part.

There are different types of feed network for feeding an array antenna. The formal array feeding networks are series or corporate feed network based on microstrip structures 17 , as shown in Fig. 1 .

( a ) Corporate and ( b ) series feed array structure 17 .

Microstrip array has a simple structure and easy fabrication proccess, which leads to compact and low-cost structures, but duo to its high losses in mmW frequency band the endfire antenna is recomanded to use 17 , 18 . Some types of passive power divider networks are Wilkinson, T-junction, and Resistive power divider. T-junction is lossless but it has two disadvanteges: un-matched at all ports and no isolation between output ports. The resistive type can be matched at all ports but it is lossy and doesn’t have isolation between output ports. But Wilkinson is lossless (if all ports are matched) and has good isolation.

In this paper Wilkinson Power Divider (WPD) has been adopted. To evaluate the WPD performance three parameters should be checked: reflection coeffcients, coupling and isolation between ports 18 . In two-way WPD, the isolation resistor is \(2{Z}_{0}\) and the impedance of λ/4 is \(\sqrt{2}{Z}_{0}\) . For equal WPD (or 3 dB) the \({Z}_{0}=50\Omega\) , the impedance of λ/4 is \(\sqrt{2}{Z}_{0}=70.7\Omega\) and isolation resistor is \({2Z}_{0}=100\Omega\) 18 . To design WPD at 28 GHz the TXline calculator is used. The substrate is Rogers RT/Duriod 5880 with 0.38 mm thickness, loss tangant of 0.0009 and relative permittivity of \({\varepsilon }_{r}=2.2\) . The values for WPD are obtained as: W 50Ω  = 1.18 mm, W 70.7Ω  = 0.65 mm and L 70.7Ω  = 1.97 mm (Fig.  2 ). The isolation resistor is 100Ω (size is 1 × 0.5 mm 2 ) from 0402 SMD family. For eight-way WPD, three stages of two ways WPD is needed. As shown in Fig.  2 , d 1 and d2 are approximately 4 times and 2 times longer than d 3 , respecivly. The distance between two output ports (d 3 ) is about \(\frac{\lambda }{2}\) to satisfy the array considerations. The performance of the eight-way designed WPD has been shown in Fig.  3 . As it can be seen reflection coeffcient, isolation and insertion loss are in acceptable range and the observed deviation from the theoritical values are due to high frequency range of operation which leads to higher microstrip line loss (conductor, dielectric and radiation losses) 18 , 19 , 20 .

Eight way Wilkinson power divider.

Simulation results of desinged eight-way WPD ( a ) reflection coeffcients, ( b ) insertion loss and ( c ) isolation.

Single elements

The design procedure of three different single elements is completely described in 21 . Figure  4 shows the structures. The substrate is RT/duriod 5880 with 15mil thickness, \({\varepsilon }_{r}=2.2\) and \({\tan}\delta =0.0009\) . The dimension of antenna1 according to Fig.  4 a are L 1  = 2.5 mm , L 2  = 5 mm L 3  = 1.615 mm , L 4  = 2.275 mm , L 5  = 1.25 mm , L 6  = 1.125 mm , W 1  = 0.4 mm , W 2  =  1.2  mm , W 3  = 0.5 mm , W 4  = 0.75 mm , W 5  = 0.5 mm , W 6  = 0.5 mm. For antenna2 the dimensions in Fig.  4 b are L 1  = 2.8 mm , L 2  = 4.22 mm L 3  = 1.068 mm , L 4  = 1.425 mm , L 5  = 1.9 mm , W 1  = 0.75 mm , W 2  = 1.25 mm , W 3  = 0.14 mm , W 4  = 0.1875 mm , W 5  = 0.25 mm. In addition, for the last one in Fig.  4 c the dimensions are L 1  = 2.5 mm , L 2  = 3.9 mm L 3  = 1.8 mm , W 1  = 0.5 mm , W 2  = 0.6 mm , W 3  = 0.6 mm . For the feeding part (which is the same for all antenna) the calculated parameters are Ls  = 3.5 mm , wt  = 3.2 mm , L  = 3.5 mm , w 1  = 1.2 mm , w  = 5.5 mm , Lt  = 1.6 mm , d  = 0.6 mm , s  = 1.2 mm . The details of the design procedure for each of the single elements and the results (simulation and fabrication) of them are reported in 21 . All of these antennas have end-fire patterns and acceptable measurmant performance but are not applicable in 5G systems due to low gain values as the single element. Moreover, regarding the Ferris equation, the path loss become higher as the frequency increases. Accordingly, to overcome the path loss in 5G mobile communication system, minimmum value of 12 dB gain is required 22 . So, the antenna array configuration is proposed to achieve the required gain value.

Structure of the proposed single element ( a ) antenna1, ( b ) antenna2 and ( c ) antenna3 21 .

Linear array antennas

Generally, the number of antenna array elements are 2 N owing to 2 N -way is beneficial structure for designing a power divider with minimum losses. In addition, impedance matching can be accomplished easily 23 . The schematics of three different array antennas are shown in Fig.  5 a–c. For better evaluation of array performance, two full-wave softwares (CST and HFSS) is used for simulation and the results of each array is shown in Fig.  5 , respectively.

The array structure and simulation results of antenna1 ( a , d , g , j ), antenna2 with measurment results ( b , e , h , k ) and antenna3 ( c , f , i , l ) and ( m ) the prototype of proposed antenna2 with SMK connector.

As it can be observed, there is a good consistency between the simulation results in both softwares. Between these three proposed antennas, antenna2 is chosen to be fabricated and tested as shown in Fig.  5 m. The connector that is used is SMK whith frequency range up to 40 GHz. So, in Fig.  5 , the measurment results are shown for antenna2, too. As it can be seen, the measurment and simulation results for antenna2 are in good agreement, which suggests that the other two antennas are also applicable in this frequency band. The diffrerences between measurement and simulation results can be considered due to substrate and specially connector losses. It is obvious that performance in high frequency range duplicates the radiation and thermal loss effect of soldiering and SMD resistors. Moreover the loss and errors of fabrication and measurement devices can not be ommited. In Fig.  6 , the simulated gain values are shown which are high enough for handheld 5G systems. Moreover, the endfire pattern of the proposed structures is suitable for 5G frequency bands because of its capabilitty (of array antenna) to consenpate the path loss. As will be discused in next section, directive antenna is a solution to minimize the SAR values in human tissue.

The 3D radiation pattern and calculated gain value of: ( a ) antenna1, ( b ) antenna2 and ( c ) antenna3.

The size of three proposed structures are presented in Table 1 which shows acceptable reflection coeffcient and gain values while keeping the overall size as minimum as possible as a good candidates for handheld 5G systems The gain values are 12.85 dB, 14.6 dB, and 12.2 dB for antenna1, antenna2, and antenna3 respectively.

SAR assessments of proposed array antennas

The 5G systems have many interesting advantages, such as higher bandwidth and data rate; hence, they are growing surprisingly in the world. However, their probably adverse effects on human body tissues from such electromagnetic sources should appraise to ensure safety of human body. Some biological effects of electromagnetic fields such as cancer, blood brain barrier, the brain tumor, Cataract, skin disease, sleep disorder have been reported 24 , 25 , 26 , 27 . The other effects of mmW frequency are genotoxicity (DNA damage), cell proliferation, gene expression, cell signaling, electrical activity, and membrane effects have been briefed in 28 . Many references can be cited in which the advantages and disadvantages of SAR and PD parameters are discussed. Some of these references prefer SAR and the others PD. It seems that this issue is still an open subject, which needs to be investigate more carefully. Owing to the following reasons in this paper, the SAR is chose. According to FCC, the power density (PD) unit is used for the distances of 5 cm or more. Therefore, it only deals with far-field exposures and does not consider the near field exposures. On the other hand, some of the mmW devices such as handsets or tablets use almost near to the head, hand or in the pocket next to the human body (in a few millimeters distances i.e. near field region) and in these conditions, the PD is not a suitable unit to evaluate the human safety. In addition, estimations based on PD do not describe the absorbed power and distributed field, but only exhibit the travelling wave in human tissues. Hence, the SAR technique is used to study 13 , 29 , 30 , 31 , 32 .

There are some limitations to assess the SAR value in human body, because the adverse biological effects may occur, so the numerical simulations are to be used for SAR evaluation. SAR is a unit to determine the rate of how much energy from electromagnetic source is absorbed per mass unit by human tissues as show in Eq. ( 1 ).

where \(\sigma\) is the conductivity of tissue in unit (S/m), E is the electric field intensity in unit (V/m), \(\rho\) is the mass density of tissue in unit (kg/m 3 ). The SAR averages either over the whole body, or over a small sample volume (typically 1 g or 10 g of tissue). The unit of SAR is watt per kilogram 21 . SAR limits in International Commission on Non-Ionizing Radiation Protection (ICNIRP) and the IEEE C95.1–2019 standards is 2 W/kg over 10 g and according to FCC standard SAR limit for 1 g is 1.6 W/kg. These limits are for the frequencies up to 10 GHz and 6 GHz respectively. The SAR limits above these two frequencies for near field exposures at mmW have not been proposed yet which is due to near field exposure at mmW. However, it is an important topic to study.

Head and handset model

To simulate the SAR parameter, a three-layer spherical human head model including skin, skull, and the brain is situated near the antenna as an exposure source. All human tissues have different permittivity ( \({\varepsilon }_{r}\) ) and conductivity ( \(\sigma\) ), and their properties depend on many parameters such as frequency, age, etc. At 28 GHz, the properties and radius of three layers are listed in Table 2 3 , 21 . The covering shell is a low loss dielectric with relative permittivity of \({\upvarepsilon }_{r}=4.5\) . The human head and handset model are shown in Fig.  7 .

( a ) Human head and handset model. ( b ) The handset dimension.

For the handset a plastic housing box with 58 × 85 × 8 mm 3 dimension is used with \({\varepsilon }_{r}=3\) and \(\sigma =0.02 \; \text{S}/\text{m}\) and 1 mm thickness in which the proposed antenna array is placed on top 33 . A glass with \({\varepsilon }_{r}=5.5\) used too as a screen of the handset 8 . The input power for the antennas in 5G systems can be set to 15 dBm, 18 dBm and 20 dBm according to FCC 34 and the distance between head and antenna are 5 mm 3 , 13 , 34 . Figure  8 . shows the results of SAR 1g and SAR 10g for 15 dBm. From this figure, it can be observed that: (1) The SAR at the nearest distance from antennas are more than others are. (2) The SAR 1g is higher than SAR 10g . (3) By increasing the distance between antenna and human head model the SAR is decreased.

Simulated SAR parameter of antenna1 (SAR 1g ( a ), SAR 10g ( d )), antenna2 (SAR 1g ( b ), SAR 10g ( e )) and antenna3 (SAR 1g ( c ), SAR 10g ( f )).

Table 3 shows the simulation results of SAR 1g and SAR 10g of three proposed array and single antennas with 15 dBm power. The single element SAR values in our published paper 21 are used in Table 3 . As can be observed, all of the simulated values are under the FCC and ICNIRP standard limits for array antennas too. Considering the same feeding part for three proposed structures and different radiating element for each, the antennas have different electric field strength (E) which leads to different SAR values according to Eq. ( 1 ).

Although all results for antenna array are larger than single elements. It can be cause by more radiation elements in array type. In the commercial SAR measurement system, a diploe antenna is used to measure the SAR parameter. For better comparison, the SAR values of these antennas i.e. proposed antennas, and dipole antenna (from 21 ) at 28 GHz are shown in Table 3 . The results of both array and single element SAR values are lower than dipole antenna, which shows that proposed end-fire (directive) antennas have lower SAR rather than common dipole antenna. In Table 4 the simulation results with 20 dBm input power are also presented. It can be seen that the values are lower than standard limits and dipole antenna too.

It is well known that electromagnetic fields can damage human tissues, thus designing the low SAR antenna is desirable for mobile devices such as handsets, which use in human body vicinity to reduce probable adverse health effects. In fact, by decreasing the SAR, the field penetration in the human tissues will decrease.

To compare the results of the SAR values and performance of three array antennas Tables 5 and 6 are provided. From the Table 5 the SAR values for proposed antennas are almost lower than the other works at 28 GHz and all of them are low SAR. From the Table 6 the proposed antennas are smaller than other references and all of them have enough gain for 5G systems.

In this paper three compact, small size, low weight, and low SAR array antennas are designed. The feeding part of them is WPD. Owing to their good patterns and reflection coefficient at 27–29.5 GHz from simulation in CST and HFSS and the measurement data, they are suitable for applying in 5G systems. Since the human health effects from electromagnetic fields is very important subject and the user are worry about it, the SAR 1g and SAR 10g of the antennas at 15 dBm (and SAR 10g at 20 dBm) have been simulated in human head model. All the results are lower the standard limits.

The distance between antenna and human head model is 5 mm. Although using hands-free increase the distance and can reduce the SAR. To more examination, results of SAR are compared with dipole antenna that use in commercial SAR measurement system. One of the methods to reduce the SAR is using of directive antenna 40 . Since our proposed antennas are end fire (directive antennas), thus, the results of SAR are suitable. It is noted that in real SAR measurement systems it is impossible to model the human head model in the layers, because the human tissue equivalent material are in jell or liquid form. Therefore, it may be said that the commercial results are not accurate and more investigation for better tissue model is necessary.

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Lak, A., Adelpour, Z., Oraizi, H. et al. Design and SAR assessment of three compact 5G antenna arrays. Sci Rep 11 , 21265 (2021). https://doi.org/10.1038/s41598-021-00679-8

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Over a Century of Array Signal Processing

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Since the introduction of phased array in 1905 by Karl Braun, a Nobel Laureate, array signal processing has advanced significantly over the past century. The era of adaptive array was started by Jack Capon, signified by his seminal paper in 1969. The Capon beamformer has better resolution and much better interference rejection capability than the data-independent beamformer by Karl Braun, provided that the array steering vector corresponding to the signal of interest (SOI) and the array covariance matrix is accurately known, and the SOI is uncorrelated to all other signals impinging on the array. However, whenever the knowledge of the SOI steering vector is imprecise, the number of data snapshots is scarce, or the SOI is correlated with a multipath, which are often the cases encountered in practice, the performance of the Capon beamformer may become worse than that of the data-independent beamformer. For over 50 years, making the Capon beamformer robust has attracted much interest and tens of thousands of papers on robust adaptive array processing have been published in the literature. To fundamentally overcome the limitations of the Capon family of beamformers, iterative approaches have been introduced in the recent literature. Most notably, the iterative adaptive approach (IAA) was published in 2010 and is shown to possess strong robustness, and can work well under single snapshot and arbitrary array scenarios. We will compare the non-parametric and user parameter free IAA algorithm with other well-known algorithms, including the data-independent beamformer, the Capon beamformer, the OMP algorithm introduced in the compressed sensing literature, as well as the parametric MUSIC and ESPRIT algorithms.

Over a Century of Array Signal Processing (8.3 MB)

• Corpus ID: 209442475

Reflectarray Antennas: Theory, Designs, and Applications Reflectarray Antennas: Theory, Designs, and Applications

• P. Nayeri , Fan Yang , A. Elsherbeni
• Published 2018
• Engineering, Physics

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Emerging Trends, Issues and Challenges for Array Signal Processing and Its Applications in Smart City

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Join the community, search results for author: ieee, found 70 papers, 12 papers with code, variational neuron shifting for few-shot image classification across domains.

no code implementations • journal 2024 • Liyun Zuo , Baoyan Wang , Lei Zhang , Jun Xu , Member , IEEE , and Xiantong Zhen

Existing meta-learning models learn the ability of learning good representation or model parameters, in order to adapt to new tasks with a few training samples.

Instance Paradigm Contrastive Learning for Domain Generalization

no code implementations • IEEE Transactions on Circuits and Systems for Video Technology 2024 • Zining Chen , Weiqiu Wang , Zhicheng Zhao , Fei Su , Member , IEEE , Aidong Men , and Yuan Dong

In this paper, we propose an instance paradigm contrastive learning framework, introducing contrast between original features and novel paradigms to alleviate domain-specific distractions.

Event-Triggered Tracking Control for Nonlinear Systems With Prescribed Performance

no code implementations • IEEE TRANSACTIONS ON SYSTEMS 2024 • Ruihang Ji , Shuzhi Sam Ge , Kai Zhao , Member , and Haizhou Li , Fellow , IEEE

Abstract—This article addresses the entry capture problem (ECP) of uncertain nonlinear systems under asymmetric performance constraints.

An Ultralightweight Hybrid CNN Based on Redundancy Removal for Hyperspectral Image Classification

no code implementations • IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2024 • Xiaohu Ma , Wuli Wang , Member , IEEE

Simultaneously, for PW-Conv, we design a spectral convolution with redundancy removal (R2Spectral-Conv).

Meta Reinforcement Learning for Multi-Task Offloading in Vehicular Edge Computing

no code implementations • TMC 2024 • Penglin Dai , Yaorong Huang , Kaiwen Hu , Xiao Wu , Huanlai Xing , and Zhaofei Yu , Member , IEEE

The objective is to design a unified solution to minimize task execution time under different MTO scenarios.

Ultra-Robust Real-Time Estimation of Gait Phase

no code implementations • IEEE Transactions on Neural Systems and Rehabilitation Engineering 2023 • Mohammad Shushtari , Hannah Dinovitzer , Jiacheng Weng , and Arash Arami , Member , IEEE

The estimator is finally tested on a participant walking with an active exoskeleton, demonstrating the robustness of D67 in interaction with an exoskeleton without being trained on any data from the test subject with or without an exoskeleton.

Interaction-Aware Planning With Deep Inverse Reinforcement Learning for Human-Like Autonomous Driving in Merge Scenarios

1 code implementation • journal 2023 • Jiangfeng Nan , Weiwen Deng , Member , IEEE , Ruzheng Zhang , Ying Wang , Rui Zhao , Juan Ding

To consider the interaction factor, the reward function for planning is utilized to evaluate the joint trajectories of the autonomous driving vehicle (ADV) and traffic vehicles.

Seismic Random Noise Attenuation Based on Non-IID Pixel-Wise Gaussian Noise Modeling

1 code implementation • IEEE Transactions on Geoscience and Remote Sensing 2023 • Chuangji Meng , Jinghuai Gao , Member , IEEE , Yajun Tian , Zhiqiang Wang

Thus, our proposed framework called VI-Non-IID inclines to have better noise characterization and generalization capabilities, which brings better performance on seismic field NA.

Spoof Trace Disentanglement for generic face antispoofing

no code implementations • journal 2023 • Yaojie Liu and Xiaoming Liu , Member , IEEE

Yet, it is a challenging task due to the diversity of spoof attacks and the lack of ground truth for spoof traces.

Bio-Inspired Feature Selection in Brain Disease Detection via an Improved Sparrow Search Algorithm

no code implementations • IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2022 • Wenyu Yu , Hui Kang , Geng Sun , Member , Shuang Liang , and Jiahui Li , Student Member , IEEE

Finally, the proposed ISSA is utilized to solve the objective function.

VCI-LSTM: Vector Choquet Integral-based Long Short-Term Memory

no code implementations • IEEE 2022 • Mikel Ferrero-Jaurrieta , Zdenko Taka ́cˇ , Javier Ferna ́ndez , Member , IEEE , Lˇubom ́ıra Horanska ́ , Grac ̧aliz Pereira Dimuro , Susana Montes , Irene D ́ıaz and Humberto Bustince , Fellow , IEEE.

Choquet integral is a widely used aggregation oper- ator on one-dimensional and interval-valued information, since it is able to take into account the possible interaction among data.

Lightweight Deep Neural Network for Joint Learning of Underwater Object Detection and Color Conversion

no code implementations • journal 2022 • Chia-Hung Yeh , Chu-Han Lin , Li-Wei Kang , Member , Chih-Hsiang Huang , Min-Hui Lin , Chuan-Yu Chang , and Chua-Chin Wang , Senior Member , IEEE

Li-Wei Kang is with the Department of Electrical Engineering, National Taiwan Normal University, Taipei 106, Taiwan (e-mail: lwkang@ntnu. edu. tw).

Topology Change Aware Data-Driven Probabilistic Distribution State Estimation Based on Gaussian Process

no code implementations • IEEE Transactions on Smart Grid 2022 • Di Cao , Member , Junbo Zhao , Weihao Hu , Senior Member , Qishu Liao , Qi Huang , Zhe Chen , Fellow , IEEE

Abstract—This paper addresses the distribution system state estimation (DSSE) with unknown topology change.

STMGCN: Mobile Edge Computing-Empowered Vessel Trajectory Prediction Using Spatio-Temporal Multigraph Convolutional Network

no code implementations • IEEE Transactions on Industrial Informatics 2022 • Ryan Wen Liu , Maohan Liang , Jiangtian Nie , Yanli Yuan , Zehui Xiong , Member , IEEE , Han Yu

—The revolutionary advances in machine learning and data mining techniques have contributed greatly to the rapid developments of maritime Internet of Things (IoT).

Coverage Control Algorithm for DSNs Based on Improved Gravitational Search

no code implementations • IEEE Sensors Journal 2022 • Yindi Yao , Huanmin Liao , Xiong Li , Student Member , IEEE , Feng Zhao , Xuan Yang , and Shanshan Hu

—In directional sensor networks (DSNs), coverage control is an important way to ensure efficient communication and reliable data transmission.

High-order Correlation Preserved Incomplete Multi-view Subspace Clustering

3 code implementations • IEEE Transactions on Image Processing 2022 • Zhenglai Li , Chang Tang , Xiao Zheng , Xinwang Liu , Senior Member , Wei zhang , Member , IEEE , and En Zhu

Specifically, multiple affinity matrices constructed from the incomplete multi-view data are treated as a thirdorder low rank tensor with a tensor factorization regularization which preserves the high-order view correlation and sample correlation.

A GAN-Based Short-Term Link Traffic Prediction Approach for Urban Road Networks Under a Parallel Learning Framework

no code implementations • IEEE Transactions on Intelligent Transportation Systems 2022 • Junchen Jin , Member , IEEE , Dingding Rong , Tong Zhang , Qingyuan Ji , Haifeng Guo , Yisheng Lv , Xiaoliang Ma , and Fei-Yue Wang

This paper proposes a short-term traffic speed prediction approach, called PL-WGAN, for urban road networks, which is considered an important part of a novel parallel learning framework for traffic control and operation.

Shallow Network Based on Depthwise Over-Parameterized Convolution for Hyperspectral Image Classification

no code implementations • 1 Dec 2021 • Hongmin Gao , Member , Zhonghao Chen , Student Member , IEEE , Chenming Li

Therefore, this letter proposes a shallow model for HSIC, which is called depthwise over-parameterized convolutional neural network (DOCNN).

Distributed Differential Evolution Based on Adaptive Mergence and Split for Large-Scale Optimization

1 code implementation • IEEE Transactions on Evolutionary Computation 2021 • Yinglan Feng , Liang Feng , Senior Member , Sam Kwong , and Kay Chen Tan , Fellow , IEEE

In this way, the number of subpopulations is adaptively adjusted and better performing subpopulations obtain more individuals.

Double Deep Q-learning Based Real-Time Optimization Strategy for Microgrids

no code implementations • 27 Jul 2021 • Hang Shuai , Xiaomeng Ai , Jiakun Fang , Wei Yao , Senior Member , Jinyu Wen , Member , IEEE

It is challenging to solve this kind of stochastic nonlinear optimization problem.

A Novel Deep Learning Method for Thermal to Annotated Thermal-Optical Fused Images

no code implementations • 13 Jul 2021 • Suranjan Goswami , IEEE Student Member , Satish Kumar Singh , Senior Member , Bidyut B. Chaudhuri , Life Fellow , IEEE

As a part of this work, we also present a new and unique database for obtaining the region of interest in thermal images based on an existing thermal visual paired database, containing the Region of Interest on 5 different classes of data.

Deep Learning Based Autonomous Vehicle Super Resolution DOA Estimation for Safety Driving

no code implementations • IEEE Transactions on Intelligent Transportation Systems 2021 • Liangtian Wan , Yuchen Sun , Lu Sun , Member , Zhaolong Ning , Senior Member , and Joel J. P. C. Rodrigues , Fellow , IEEE

Abstract— In this paper, a novel system architecture including a massive multi-input multi-output (MIMO) or a reconfigurable intelligent surface (RIS) and multiple autonomous vehicles is considered in vehicle location systems.

Content-Preserving Image Stitching with Piecewise Rectangular Boundary Constraints

no code implementations • IEEE Transactions on Visualization and Computer Graphics 2021 • Yun Zhang , Yu-Kun Lai , and Fang-Lue Zhang , Member , IEEE

By analyzing the irregular boundary, we construct a piecewise rectangular boundary.

Deep Reinforcement Learning Based Optimization for IRS Based UAV-NOMA Downlink Networks

no code implementations • 17 Jun 2021 • Shiyu Jiao , Ximing Xie , Zhiguo Ding , Fellow , IEEE

This paper investigates the application of deep deterministic policy gradient (DDPG) to intelligent reflecting surface (IRS) based unmanned aerial vehicles (UAV) assisted non-orthogonal multiple access (NOMA) downlink networks.

Detailed Primary and Secondary Distribution System Model Enhancement Using AMI Data

no code implementations • 29 May 2021 • Karen Montano-Martinez , Sushrut Thakar , Shanshan Ma , Zahra Soltani , Student Member , Vijay Vittal , Life Fellow , Mojdeh Khorsand , Raja Ayyanar , Senior Member , Cynthia Rojas , Member , IEEE

Reliable and accurate distribution system modeling, including the secondary network, is essential in examining distribution system performance with high penetration of distributed energy resources (DERs).

Context-aware taxi dispatching at city-scale using deep reinforcement learning

no code implementations • IEEE Transactions on Intelligent Transportation Systems 2021 • Zhidan Liu , Jiangzhou Li , and Kaishun Wu , Member , IEEE

Abstract— Proactive taxi dispatching is of great importance to balance taxi demand-supply gaps among different locations in a city.

Low-Complexity Symbol Detection and Interference Cancellation for OTFS System

no code implementations • 期刊 2021 • Huiyang Qu , Guanghui Liu , Lei Zhang , Shan Wen , Graduate Student Member , and Muhammad Ali Imran , Senior Member , IEEE

Orthogonal time frequency space (OTFS) is a two-dimensional modulation scheme realized in the delay- Doppler domain, which targets the robust wireless transmissions in high-mobility environments.

Multi-Scale and Multi-Direction GAN for CNN-Based Single Palm-V ein Identification

no code implementations • IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY 2021 • Huafeng Qin , Mounim A. El-Y acoubi , Y a n t a o L i , Member , IEEE , and Chongwen Liu

Despite recent advances of deep neural networks in hand vein identification, the existing solutions assume the availability of a large and rich set of training image samples.

Joint Trajectory and Power Allocation Design for Secure Artificial Noise Aided UAV Communications

no code implementations • journals 2021 • Milad Tatar Mamaghani , Graduate Student Member , and Yi Hong , Senior Member , IEEE

This paper investigates an average secrecy rate (ASR) maximization problem for an unmanned aerial vehicle (UAV) enabled wireless communication system, wherein a UAV is employed to deliver confidential information to a ground destination in the presence of a terrestrial passive eavesdropper.

A 510-nW Wake-Up Keyword-Spotting Chip Using Serial-FFT-Based MFCC and Binarized Depthwise Separable CNN in 28-nm CMOS

no code implementations • journal 2021 • Weiwei Shan , Minhao Yang , Tao Wang , Yicheng Lu , Hao Cai , Lixuan Zhu , Jiaming Xu , Chengjun Wu , Longxing Shi , Senior Member , and Jun Yang , Member , IEEE

We propose a sub-µW always-ON keyword spotting (µKWS) chip for audio wake-up systems.

Data-Driven Assisted Chance-Constrained Energy and Reserve Scheduling with Wind Curtailment

no code implementations • 2 Nov 2020 • Xingyu Lei , Student Member , Zhifang Yang , Member , Junbo Zhao , Juan Yu , Senior Member , IEEE

Case studies performed on the PJM 5-bus and IEEE 118-bus systems demonstrate that the proposed method is capable of accurately accounting the influence of wind curtailment dispatch in CCO.

Systems and Control Systems and Control

CRPN-SFNet: A High-Performance Object Detector on Large-Scale Remote Sensing Images

no code implementations • 28 Oct 2020 • QiFeng Lin , Jianhui Zhao , Gang Fu , and Zhiyong Yuan , Member , IEEE

Extensive experiments on the public Dataset for Object deTection in Aerial images data set indicate that our CRPN can help our detector deal the larger image faster with the limited GPU memory; meanwhile, the SFNet is beneficial to achieve more accurate detection of geospatial objects with wide-scale range.

Frame-wise Cross-modal Matching for Video Moment Retrieval

1 code implementation • 22 Sep 2020 • Haoyu Tang , Jihua Zhu , Meng Liu , Member , IEEE , Zan Gao , Zhiyong Cheng

Another contribution is that we propose an additional predictor to utilize the internal frames in the model training to improve the localization accuracy.

Attention Transfer Network for Nature Image Matting

1 code implementation • IEEE Transactions on Circuits and Systems for Video Technology 2020 • Fenfen Zhou , Yingjie Tian , Member , IEEE , and Zhiquan Qi

Then, we introduce a scale transfer block to magnify the feature maps without adding extra information.

A New Multiple Source Domain Adaptation Fault Diagnosis Method between Different Rotating Machines

no code implementations • TRANSACTIONS ON INDUSTRIAL INFORMA TICS 2020 • un Zhu , Nan Chen , Member , IEEE , and Changqing Shen

To solve this issue, transfer learning is proposed by leveraging knowl- edge learned from source domain to target domain.

Learning Person Re-identification Models from Videos with Weak Supervision

no code implementations • 21 Jul 2020 • Xueping Wang , Sujoy Paul , Dripta S. Raychaudhuri , Min Liu , Yaonan Wang , Amit K. Roy-Chowdhury , Fellow , IEEE

In order to cope with this issue, we introduce the problem of learning person re-identification models from videos with weak supervision.

Obstacle Avoidance and Tracking Control of Redundant Robotic Manipulator: An RNN-Based Metaheuristic Approach

no code implementations • IEEE Transactions on Industrial Informatics 2020 • Ameer Hamza Khan , Student Member , Shuai Li , and Xin Luo , Senior Member , IEEE

In this article, we present a metaheuristic-based control framework, called beetle antennae olfactory recurrent neural network, for simultaneous tracking control and obstacle avoidance of a redundant manipulator.

Edge server deployment scheme of blockchain in IoVs

no code implementations • 16 Jun 2020 • Liya Xu , Mingzhu Ge , Weili Wu , Member , IEEE

In fact, the application of blockchain in IoVs can be implemented by employing edge computing.

Service Provisioning Framework for RAN Slicing: User Admissibility, Slice Association and Bandwidth Allocation

no code implementations • IEEE Transactions on Mobile Computing 2020 • Yao Sun , Shuang Qin , Member , Gang Feng , Lei Zhang , and Muhammad Ali Imran , SeniorMember , IEEE

Network slicing (NS) has been identified as one of the most promising architectural technologies for future mobile network systems to meet the extremely diversified service requirements of users.

A Simplified 2D-3D CNN Architecture for Hyperspectral Image Classification Based on Spatial–Spectral Fusion

no code implementations • 5 Jun 2020 • Chunyan Yu , Rui Han , Meiping Song , Caiyu Liu , and Chein-I Chang , Life Fellow , IEEE

Abstract—Convolutional neural networks (CNN) have led to a successful breakthrough for hyperspectral image classification (HSIC).

Decision Fusion in Space-Time Spreading aided Distributed MIMO WSNs

no code implementations • 16 May 2020 • I. Dey , H. Joshi , Member , N. Marchetti , Senior Member , IEEE

In this letter, we propose space-time spreading (STS) of local sensor decisions before reporting them over a wireless multiple access channel (MAC), in order to achieve flexible balance between diversity and multiplexing gain as well as eliminate any chance of intrinsic interference inherent in MAC scenarios.

Energy-Efficient Over-the-Air Computation Scheme for Densely Deployed IoT Networks

no code implementations • IEEE 2020 • Semiha Tedik Basaran , Student Member , Gunes Karabulut Kurt , and Periklis Chatzimisios , Senior Member , IEEE

The proposed MMSE estimator provides a signif- icant mean squared error improvement with reducing en- ergy consumption compared to the conventional estimator.

A Lightweight and Privacy-Preserving Authentication Protocol for Mobile Edge Computing

no code implementations • 27 Feb 2020 • Kuljeet Kaur∗ , Sahil Garg∗ , Georges Kaddoum∗ , Member , Mohsen Guizani† , Fellow , IEEE , and Dushantha Nalin K. Jayakody‡ , Senior Member , IEEE.

With the advent of the Internet-of-Things (IoT), vehicular networks and cyber-physical systems, the need for realtime data processing and analysis has emerged as an essential pre-requite for customers’ satisfaction.

Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement Learning

1 code implementation • 24 Feb 2020 • Chongwen Huang , Member , IEEE , Ronghong Mo , Chau Yuen , Senior Member

In this paper, we investigate the joint design of transmit beamforming matrix at the base station and the phase shift matrix at the RIS, by leveraging recent advances in deep reinforcement learning (DRL).

Reinforcement Learning Tracking Control for Robotic Manipulator With Kernel-Based Dynamic Model

no code implementations • TRANSACTION 2020 • Yazhou Hu , Wenxue Wang , Hao liu , and Lianqing Liu , Member , IEEE

In this algorithm, a reward function is defined according to the features of tracking control in order to speed up the learning process, and then an RL tracking controller with a kernel-based transition dynamic model is proposed.

Broad Learning System Based on Maximum Correntropy Criterion

no code implementations • 24 Dec 2019 • Yunfei Zheng , Badong Chen , Shiyuan Wang , Senior Member , Weiqun Wang , Member , IEEE

As an effective and efficient discriminative learning method, Broad Learning System (BLS) has received increasing attention due to its outstanding performance in various regression and classification problems.

Localization and Clustering Based on Swarm Intelligence in UAV Networks for Emergency Communications

no code implementations • IEEE Internet of Things Journal 2019 • Muhammad Yeasir Arafat , Sangman Moh , Member , IEEE

Second, we propose an energy-efficient swarm-intelligence-based clustering (SIC) algorithm based on PSO, in which the particle fitness function is exploited for inter-cluster distance, intra-cluster distance, residual energy, and geographic location.

GETNET: A General End-to-end Two-dimensional CNN Framework for Hyperspectral Image Change Detection

1 code implementation • 5 May 2019 • Qi. Wang , Senior Member , Zhenghang Yuan , Qian Du , Xuelong. Li , Fellow , IEEE

In order to better handle high dimension problem and explore abundance information, this paper presents a General End-to-end Two-dimensional CNN (GETNET) framework for hyperspectral image change detection (HSI-CD).

VSSA-NET: Vertical Spatial Sequence Attention Network for Traffic Sign Detection

no code implementations • 5 May 2019 • Yuan Yuan , Zhitong Xiong , Student Member , Qi. Wang , Senior Member , IEEE

Our contributions are as follows: 1) We propose a multi-resolution feature fusion network architecture which exploits densely connected deconvolution layers with skip connections, and can learn more effective features for the small size object; 2) We frame the traffic sign detection as a spatial sequence classification and regression task, and propose a vertical spatial sequence attention (VSSA) module to gain more context information for better detection performance.

Discrete-Time Impulsive Adaptive Dynamic Programming

no code implementations • IEEE Transactions on Cybernetics 2019 • Qinglai Wei , Ruizhuo Song , Member , IEEE , Zehua Liao , Benkai Li , and Frank L. Lewis

Abstract—In this paper, a new iterative adaptive dynamic programming (ADP) algorithm is developed to solve optimal impulsive control problems for infinite horizon discrete-time nonlinear systems.

Generalization of the Dark Channel Prior for Single Image Restoration

no code implementations • IEEE Transactions on Image Processing 2019 • Yan-Tsung Peng , Keming Cao , and Pamela C. Cosman , Fellow , IEEE

Abstract— Images degraded by light scattering and absorption, such as hazy, sandstorm, and underwater images, often suffer color distortion and low contrast because of light traveling through turbid media.

A MIP Model for Risk Constrained Switch Placement in Distribution Networks

no code implementations • IEEE 2019 • Milad Izadi , Student Member , IEEE and Amir Safdarian , Member , IEEE

The model is applied to the RBTS-Bus4 and a real distribution network.

PEA265: Perceptual Assessment of Video Compression Artifacts

no code implementations • 1 Mar 2019 • Liqun Lin , Shiqi Yu , Tiesong Zhao , Member , Zhou Wang , Fellow , IEEE

To monitor and improve visual QoE, it is crucial to develop subjective and objective measures that can identify and quantify various types of PEAs.

A Provably Secure and Efficient Identity-Based Anonymous Authentication Scheme for Mobile Edge Computing

no code implementations • 22 Feb 2019 • Xiaoying Jia，Debiao He , Neeraj Kumar , and Kim-Kwang Raymond Choo , Senior Member , IEEE

Mobile edge computing (MEC) allows one to overcome a number of limitations inherent in cloud computing, although achieving the broad range of security requirements in MEC settings remains challenging.

Location-Centered House Price Prediction: A Multi-Task Learning Approach

no code implementations • 7 Jan 2019 • Guangliang Gao , Zhifeng Bao , Jie Cao , A. K. Qin , Timos Sellis , Fellow , IEEE , Zhiang Wu

Regarding the choice of prediction model, we observe that a variety of approaches either consider the entire house data for modeling, or split the entire data and model each partition independently.

DATS: Dispersive Stable Task Scheduling in Heterogeneous Fog Networks

no code implementations • Conference 2018 • Zening Liu , Xiumei Yang , Yang Yang , Kunlun Wang , and Guoqiang Mao , Fellow , IEEE

Abstract—Fog computing has risen as a promising architecture for future Internet of Things (IoT), 5G and embedded artificial intelligence (AI) applications with stringent service delay requirements along the cloud to things continuum.

Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks

no code implementations • IEEE INTERNET OF THINGS JOURNAL, VOL. 6, NO. 3 2018 • Jiawen Kang , Rong Y u , Xumin Huang , Maoqiang Wu , Sabita Maharjan , Member , Shengli Xie , and Y an Zhang , Senior Member , IEEE

Due to limited resources with vehicles, vehicular edge computing and networks (VECONs) i. e., the integration of mobile edge computing and vehicular networks, can provide powerful computing and massive storage resources.

Optimal Training for Residual Self-Interference for Full-Duplex One-Way Relays

no code implementations • 13 Aug 2018 • Xiaofeng Li , Cihan Tepedelenlio˘glu , and Habib ¸Senol , Member , IEEE

For the former, we propose a training scheme to estimate the overall channel, and for the latter the CRB and the optimal number of relays are derived when the distance between the source and the destination is fixed.

Medical Image Synthesis with Deep Convolutional Adversarial Networks

1 code implementation • IEEE Transactions on Biomedical Engineering 2018 • Dong Nie , Roger Trullo , Jun Lian , Li Wang , Caroline Petitjean , Su Ruan , Qian Wang , and Dinggang Shen , Fellow , IEEE

To better model a nonlinear mapping from source to target and to produce more realistic target images, we propose to use the adversarial learning strategy to better model the FCN.

Single Image Dehazing Using Color Ellipsoid Prior

1 code implementation • IEEE Transactions on Image Processing 2018 • Trung Minh Bui , Student Member , and Wonha Kim , Senior Member , IEEE

The proposed method constructs color ellipsoids that are statistically fitted to haze pixel clusters in RGB space and then calculates the transmission values through color ellipsoid geometry.

Significantly Fast and Robust Fuzzy C-MeansClustering Algorithm Based on MorphologicalReconstruction and Membership Filtering

no code implementations • IEEE 2018 • Tao Lei , Xiaohong Jia , Yanning Zhang , Lifeng He , Hongy-ing Meng , Senior Member , and Asoke K. Nandi , Fellow , IEEE

However, the introduction oflocal spatial information often leads to a high computationalcomplexity, arising out of an iterative calculation of the distancebetween pixels within local spatial neighbors and clusteringcenters.

An Integrated Platform for Live 3D Human Reconstruction and Motion Capturing

no code implementations • 8 Dec 2017 • Dimitrios S. Alexiadis , Anargyros Chatzitofis , Nikolaos Zioulis , Olga Zoidi , Georgios Louizis , Dimitrios Zarpalas , Petros Daras , Senior Member , IEEE

The latest developments in 3D capturing, processing, and rendering provide means to unlock novel 3D application pathways.

Robust Single Image Super-Resolution via Deep Networks With Sparse Prior

1 code implementation • journals 2016 • Ding Liu , Zhaowen Wang , Bihan Wen , Student Member , Jianchao Yang , Member , Wei Han , and Thomas S. Huang , Fellow , IEEE

We demonstrate that a sparse coding model particularly designed for SR can be incarnated as a neural network with the merit of end-to-end optimization over training data.

A Decentralized Cooperative Control Scheme With Obstacle Avoidance for a Team of Mobile Robots

no code implementations • journal 2013 • Hamed Rezaee , Student Member , and Farzaneh Abdollahi , Member , IEEE

The problem of formation control of a team of mobile robots based on the virtual and behavioral structures is considered in this paper.

A Grid-Based Evolutionary Algorithm for Many-Objective Optimization

1 code implementation • IEEE Transactions on Evolutionary Computation 2013 • Shengxiang Yang , Member , IEEE , Miqing Li , Xiaohui Liu , and Jinhua Zheng

Balancing convergence and diversity plays a key role in evolutionary multiobjective optimization (EMO).

Physiological Parameter Monitoring from Optical Recordings with a Mobile Phone

no code implementations • 29 Jul 2011 • Christopher G. Scully , Student Member , Jinseok Lee , Joseph Meyer , Alexander M. Gorbach , Domhnull Granquist-Fraser , Yitzhak Mendelson , Member , and Ki H. Chon , Senior Member , IEEE

We show that a mobile phone can serve as an accurate monitor for several physiological variables, based on its ability to record and analyze the varying color signals of a fingertip placed in contact with its optical sensor.

Performance Analysis of Two Hop Amplify-and-Forward Systems with Interference at the Relay

no code implementations • journal 2010 • Himal A. Suraweera , Member , HariK.Garg , and A. Nallanathan , Senior Member , IEEE

Abstract—We analyze the performance of a two hop channel state information (CSI)-assisted amplify-and-forward system, with co-channel interference at the relay.

Efficiently Indexing Large Sparse Graphs for Similarity Search

no code implementations • 18 Feb 2010 • Guoren Wang , Bin Wang , Xiaochun Yang , IEEE Computer Society , and Ge Yu , Member , IEEE

Abstract—The graph structure is a very important means to model schemaless data with complicated structures, such as protein- protein interaction networks, chemical compounds, knowledge query inferring systems, and road networks.

ANALYSIS OF CALIBRATED SEA CLUTTER AND BOAT REFLECTIVITY DATA AT C- AND X-BAND IN SOUTH AFRICAN COASTAL WATERS

no code implementations • IEEE 2007 • Ron Rubinstein , Member , Tomer Peleg , Student Member , and Michael Elad , Fellow , IEEE

Abstract—The synthesis-based sparse representation model for signals has drawn considerable interest in the past decade.

Parameter-free Geometric Document Layout Analysis

no code implementations • IEEE Transactions on Pattern Analysis and Machine Intelligence 2001 • Seong-Whan Lee , Senior Member , IEEE , and Dae-Seok Ryu

Based on the proposed periodicity measure, multiscale analysis, and confirmation procedure, we could develop a robust method for geometric document layout analysis independent of character font sizes, text line spacing, and document layout structures.

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