Abstract The separation of overlapping components is a well-known and difficult problem in multicomponent signals analysis and it is shared by applications dealing with radar, biosonar, seismic, and audio signals. In order to estimate the instantaneous frequencies of a multicomponent signal, it is necessary to disentangle signal modes in a proper domain. Unfortunately, if signal modes supports overlap

In this letter, we improve lossless intra-frame compression of color filter array (CFA) video based on Camera-Aware Multi-Resolution Analysis (CAMRA). CAMRA-based compression leverages the correlation between LH and HL subbands of wavelet-transformed CFA video frames. The key contribution of this letter is an analysis showing that the chrominance components shared by LH and HL subbands of LeGall 5/3

A raw image captured by a color filter array (CFA), such as a Bayer pattern, is usually compressed after demosaicing with some processings (denoising, deblurring, tone-mapping, and so on). However, since photographers, designers, and high-end users prefer to work with the raw image sampled by CFA (referred to as “raw image”) directly, a raw image should be compressed before demosaicing. For effective

With the advance in wireless network technique, its security becomes of paramount importance. Radio Frequency Fingerprint (RFF) is the underlying characteristic of hardware chains in transmitters, which can be used as a unique ID for specific emitter identification (SEI) and a non-cryptographic access authentication technology in physical layer to enhance wireless network security. To date, few studies

In this letter, a novel kernel function named $q$ -Rényi kernel is proposed. Based on it, a new online adaptive learning algorithm is presented, which is derived based on the recursive adaptive filtering paradigm under the reproducing kernel Hilbert space. The proposed learning algorithm is different from the conventional kernel-based learning paradigm in two senses: first, the reproducing kernel so-called

Different from traditional image super-resolution task, real image super-resolution(Real-SR) focus on the relationship between real-world high-resolution(HR) and low-resolution(LR) image. Most of the traditional image SR obtains the LR sample by applying a fixed down-sampling operator. Real-SR obtains the LR and HR image pair by incorporating different quality optical sensors. Generally, Real-SR has

With the advance in content-based image retrieval and the popularity of Data-as-a-Service, enterprises can outsource their image retrieval systems on cloud platforms to reduce heavy storage, computation, and communication burdens. However, this brings many privacy problems. Although several privacy-preserving image retrieval schemes have been proposed to protect users’ privacy, they have two major

Abstract With the development of unmanned aerial vehicle (UAV), it has been used in many fields, such as aerial photography, military, and transportation. However, it is a challenge for charging due to its short battery life. Wireless charging has been considered as a good UAV solution. In this paper, we proposed a wireless power transmission system (WPT) through inductive coupling and analyzed the

Abstract With the development of wireless LAN (WLAN) technology, wireless access points (APs) are deployed increasingly more and the number of mobile terminals is increasing. It is normal for a mobile terminal to hand over its AP. The traditional terminal handover method cannot effectively control the handover delay and balance the network load due to the inherent drawbacks such as closed encapsulation

Abstract A new variable step-size strategy for the least mean square (LMS) algorithm is presented for distributed estimation in adaptive networks using the diffusion scheme. This approach utilizes the ratio of filtered and windowed versions of the squared instantaneous error for iteratively updating the step-size. The result is that the dependence of the update on the power of the error is reduced

The paper extends our earlier work on the sum of a complex Gaussian and the product of two complex Gaussians (a scalar and a vector) by incorporating multiple targets. We derive the joint probability density function (pdf) of the resulting vector, after which we derive the pdf, cumulative distribution function (cdf), and moments of the square norm of the vector (signal energy). A novel integral function

Video retargeting is a technique used to transform a given video to a target aspect ratio. Current methods often cause severe visual distortion due to frequent temporal incoherence during the retargeting. In this study, we propose a new extrapolation-based video retargeting method using an image-to-warping vector generation network to maintain temporal coherence and prevent deformation of an input

Recent work has shown the effectiveness of the plug-and-play priors (PnP) framework for regularized image reconstruction. However, the performance of PnP depends on the quality of the denoisers used as priors. In this letter, we design a novel PnP denoising prior, called multiple self-similarity net (MSSN), based on the recurrent neural network (RNN) with self-similarity matching using multi-head attention

Generalized Zero-shot learning (GZSL) for object recognition is to solve the problem of recognizing samples in both seen and unseen classes, while only having seen classes in training. As labeling abundant examples for all kinds of classes in realistic scenarios is costly and impractical, GZSL has become a novel and hot field of research in recent years. Most previous methods tried to learn a fixed

Image compression systems that exploit the properties of the human visual system have been studied extensively over the past few decades. For the JPEG2000 image compression standard, all previous methods that aim to optimize perceptual quality have considered the irreversible pipeline of the standard. In this work, we propose an approach for the reversible pipeline of the JPEG2000 standard. We introduce

Lane detection is a useful technique in modern autonomous vehicles systems, which assists vehicle to accurately localize itself according to detected road lines. Traditional methods leveraged edge detection and Hough transform based algorithms to plot lines along the detected lane. Noticeably, they did not take the informative feature road gradient into account. In addition, most previous deep learning-based

Human action recognition plays an important role in modern intelligent systems, such as human–computer interaction (HCI), sport analysis, and somatosensory game. Compared with conventional 2-D based human action analysis, using Kinect sensor can obtain depth information of human action, which is significant for human action recognition. In this paper, we propose a joint angle sequence model for recognizing

The task of object tracking is very important since its various applications. However, most object tracking methods are based on visible images, which may fail when visible images are unreliable, for example when the illumination conditions are poor. To address this issue, in this paper a fusion tracking method which combines information from RGB and thermal infrared images (RGB-T) is presented based

In sport sceneries, automatically recognizing human actions is a useful technique that can be popularly applied in may domains, such as human body tracking and athlete behavior analysis Most state-of-the-art deep architectures have achieved competitive performance in recognizing human action. However, it is still a challenging task due to the unavoidable occlusion, camera angle changes, and varied

Target recognition is a key module in modern human–computer interaction (HCI) and computer vision systems It is pervasively used in many domains like autonomous vehicles and robot, remote operation, and video surveillance. However, due to the complicated environment and object occlusion, target recognition is still a challenging task. In this paper, we propose a novel target recognition algorithm toward

Detecting and understanding human action under sophisticated lighting condition and backgrounds, also known as human action recognition in real-world context, is an indispensable component in modern intelligent systems and has becoming a hot research topic currently. Nowadays, human action recognition is still a tough challenge due to intra-class and inter-class, environment and temporal-level differences

Intelligently tracking objects with varied shapes, color, lighting conditions, and backgrounds is an extremely useful application in many HCI applications, such as human body motion capture, hand gesture recognition, and virtual reality (VR) games. However, accurately tracking different objects under uncontrolled environments is a tough challenge due to the possibly dynamic object parts, varied lighting

Image shadow detection and removal can effectively recover image information lost in the image due to the existence of shadows, which helps improve the accuracy of object detection, segmentation and tracking. Thus, aiming at the problem of the scale of the shadow in the image, and the inconsistency of the shadowed area with the original non-shadowed area after the shadow is removed, the multi-scale

In this paper, a novel method for lossless image encryption based on set partitioning in hierarchical trees and cellular automata. The proposed encryption method embeds the encryption into the compression process, in which a small part of the data is encrypted quickly, while maintaining the good coding characteristics of set partitioning in hierarchical trees (SPIHT). The proposed encryption system

Rate Distortion Optimization (RDO) is employed in High-Efficiency Video Coding (HEVC) to enhance its coding efficiency. Owing to its coding complexity, RDO is traditionally performed within each frame with fixed quantization parameters (QPs), without fully considering the coding dependencies between the current frame and future frames within a temporal propagation chain. To improve the coding efficiency

Emotion recognition is a hot research in modern intelligent systems. The technique is pervasively used in autonomous vehicles, remote medical service, and human–computer interaction (HCI). Traditional speech emotion recognition algorithms cannot be effectively generalized since both training and testing data are from the same domain, which have the same data distribution. In practice, however, speech

Fitting a model to data contaminated by noise and outliers is a common task in computer vision, and it is often solved by maximizing inlier set. Most existing methods cannot guarantee global optimality, due to the two techniques widely utilized in inlier maximization: randomized sampling to generate candidate models and a hard threshold on residuals to classify inliers and outliers. In this paper,

In recent years, hyperspectral image super-resolution has attracted the attention of many researchers and has become a hot topic in the field of computer vision. However, it is difficult to obtain high-resolution images due to imaging hardware devices. At present, many existing hyperspectral image super-resolution methods have not achieved good results. In this paper, we propose a hyperspectral image

Considering the image captioning problem, it is difficult to correctly extract the global features of the images. At the same time, most attention methods force each word to correspond to the image region, ignoring the phenomenon that words such as “the” in the description text cannot correspond to the image region. To address these problems, an adaptive attention model with a visual sentinel is proposed

Video-based person re-identification (Re-ID) is of important capability for artificial intelligence and human–computer interaction. The spatial and temporal features play indispensable roles to comprehensively represent the person sequences. In this paper, we propose a comprehensive feature fusion mechanism (CFFM) for video-based Re-ID. We use multiple significance-aware attention to learn attention-based

This paper presents an effective hand-crafted texture operator for texture recognition, referred to as oriented star sampling structure based multi-scale ternary pattern (O3S-MTP) which is expected to better represent salient local texture structure. Instead of heuristic code constructions, the proposed O3S-MTP descriptor is defined as a gray-scale invariant texture measure, derived from a general

In this work, we explore the feasibility and rationality of the glove-type massage information acquisition system combined with the pneumatic human organ simulator in the traditional massage context. We proposed the glove-type massage information acquisition system and the pneumatic human organ simulator to compare and analyze the effectiveness of the compression displacement, stiffness, and pressure

With the rapid development of computer vision and multimedia technology, especially the visual tracking technology and network transmission, teacher-centered education is popular nowadays. The shortcomings of the conventional classroom teaching mode by manually student behavior analysis are gradually becoming less effective. Aiming at the main problems existing in the application of classroom teaching

Human action recognition is the key technique in many modern intelligent systems, such as video surveillance, sport motion analysis, virtual reality, and shopping behavior analysis. Human action recognition is a challenging task due to the sophisticated backgrounds and possible occlusions In this paper, we aim to recognize human actions from the video stream of sport scenes by intelligently fusing

Abstract Minimizing total harmonic distortion (THD) with less system complexity and computation time is a stringent constraint for many power systems. The multilevel inverter can have low THD when switching angles are selected at the fundamental frequency. For low-order harmonic minimization, selective harmonic elimination (SHE) is the most adopted and proficient technique but it involves the non-linear

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This Special Issue of the IEEE Journal on Emerging and Selected Topics in Circuits and Systems (JETCAS) is dedicated to novel contributions to the field of programmable metamaterials. Recent years have witnessed the emergence of this paradigm, whereby the electromagnetic response of the metamaterial can be encoded into a string of bits. This allows to control electromagnetic waves using well-defined

Metamaterials and their two-dimensional analogues, metasurfaces, have recently attracted enormous attention because of their powerful control over electromagnetic (EM) waves from microwave to visible range. Moreover, by introducing explicit control of its sub-wavelength unit cells, a metamaterial can become programmable. Programmable metamaterials may not only host multiple EM functionalities that

Active metasurfaces pave a way for manipulating electromagnetic (EM) waves in real-time by incorporating with tunable materials or components, emerging as an attractive solution to achieve versatile EM functionalities in dynamic fashions. However, most of the active metasurfaces demonstrated so far only support tunable responses for a certain single frequency band, or have obvious frequency cross-talks

Electromagnetic (EM) beams carrying orbital angular momentum (OAM) are of great importance in modern wireless communications due to their attractive properties of self-reconstruction and multiplexing multiple beams. However, they are hardly deployed in a real-world scenario since they cannot be dynamically generated in a real-time and low-cost way, especially for the case of topological charges more

This paper proposes a method for converting a large existing surface into a programmable wireless charger, capable of distributing energy efficiently at multiple locations on demand and charge different types of devices. The key innovation here is to combine magnetic resonance-based energy transfer with the so called concept of ‘energy hopping’ across wireless inter-connected coils, where the magnetic

In this paper, a comprehensive study of millimeter-wave (mmW) imaging for far-field and near-field objects using 1-bit programmable metasurface (PMS) is presented. Theoretical PMS imaging simulation models are proposed by using plane-wave angular spectrum approach, in which two simulation models based on the flexible mmW beam-forming of PMS are developed. The first imaging model steers the high-gain

Recent years have seen the emergence of programmable metasurfaces, where the user can modify the electromagnetic (EM) response of the device via software. Adding reconfigurability to the already powerful EM capabilities of metasurfaces opens the door to novel cyber-physical systems with exciting applications in domains such as holography, cloaking, or wireless communications. This paradigm shift, however

Digital Metasurfaces have recently offered tremendous opportunities in real-time manipulation of terahertz (THz) waves in programmable ways to reach special applications that cannot be achieved using conventional architectures. Unlike the previous demonstrations at this spectrum, which only exploit spatial modulation, in this paper, we propose a spatiotemporally modulated graphene-based digital metasurface

Software-Defined Metamaterials (SDMs) are envisioned to enable the control of electromagnetic waves at an unprecedented scale. Various SDM applications will require downlink and broadcast-based transmission of control packets from a powered transmitter to energy harvesting nanonodes. The nanonode’s communication system is anticipated to be a bottleneck for such nanonetworks, hence an accurate modeling

On-chip wireless links offer improved network performance due to long distance communication, additional bandwidth, and broadcasting capabilities of antennas. This work challenges the on-chip antenna design conventions, and pushes toward a Through-Silicon Via-based antenna design called TSV_A that establishes multi-band wireless communication through the silicon substrate medium with only a 3 dB loss

Programmable metasurfaces have recently been proposed to dynamically manipulate electromagnetic (EM) waves in both temporal and spatial dimensions. With active components integrated into unit cells of the metasurface, states of the unit cells can be adjusted by digital codes. The metasurface can then construct complex spatial and temporal electromagnetic beams. Given the main parameters of the beam

Metasurfaces and metamaterials are playing a growing role in the control of electromagnetic waves in the application of communication, display, and sensing technologies. However, designing photonic structures as the building blocks of these systems is typically a tedious trial-and-error process that requires extensive simulations with iterative sweeps in a multi-dimensional parameter space. To circumvent

A fast analytical method for calculating the radiation pattern of solar antennas (SOLANTs) consisting of metasurface-based solar cells is proposed. The proposed method is able to analyse both uniform and non-uniform metasurfaces. In the developed method, the reciprocity theorem along with the transmission line model is used to model the layered structure used in the design of SOLANTs. To model the

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In this letter, the computation of the Green's function for one-dimensional (1-D) periodic structures is presented via a fast and accurate algorithm based on the philosophy of Kummer's decomposition (KD). The KD uses an optimal value for a quasi-periodicity parameter. An approximate optimal balance between direct summation and acceleration is constructed when necessary. The algorithm has been designed

In this letter, a three-dimensionally printed one-sixteenth fractional spherical homogeneous dielectric lens antenna on a metallic corner reflector is designed. This lens antenna is fed by an open-ended rectangular waveguide for high-gain radiation. The main design concept is to produce an equivalent spherical dielectric lens that is excited by multiple virtual sources arising from the multiple images

A low-profile wideband dual-polarized antenna with an improved high-impedance surface (HIS) reflector is proposed. Dual-polarized radiation is excited by feeding a set of crossed dipoles. Low profile is achieved by utilizing an improved HIS reflector. Good impedance characteristics are realized by inserting small square cells among the primary hexagonal cells of the HIS. Two shorting pins and four

In this letter, a novel circularly polarized (CP) slotted substrate integrated waveguide (SIW) cavity antenna using a hybrid TE 202 mode (HTM) and the eigen TE 202 mode (ETM) is proposed and studied. The antenna is designed for Ku-band satellite wireless link applications. It utilizes two different and orthogonal TE 202 modes (ETM and HTM) with slots etched on the surface to form left-hand CP radiation

Three wideband monopolar patch antennas (MPAs) integrated into a Y-shape structure for multi-input–multi-output (MIMO) operation in 3300–4200 MHz for fifth-generation (5G) access points are presented in this letter. Each MPA has an antenna height of 10 mm (about 0.11 λ at 3300 MHz) and a top-patch length of 22 mm (about 0.24 λ at 3300 MHz). Each MPA is capacitively excited through a feed strip at its

A novel very low frequency (VLF) communication system using one pair of magnetoelectric (ME) antennas has been proposed. The ME antennas are strain-mediated acoustic resonators operating at their electromechanical resonance in the VLF band. The measured near-field radiation pattern reveals ME antennas are equivalent to dipole antennas. The magnetic field radiated by the ME transmitter has been predicted