Uniform phase empirical mode decomposition (UPEMD) is an effective signal separation method, which is proposed to solve the mode mixing phenomenon of empirical mode decomposition (EMD) by adding uniform phase sinusoidal signal as masking signal. However, the decomposition effect of UPEMD depends on the selection of amplitude and phase number of masking signal. Besides, there are also some issues such

Many real world systems ranging from biological to social systems can be modeled as networks. As network data becomes more ubiquitous, it is important to reduce the large-scale networks into smaller modules or communities. Most of the original research in community detection has focused on static networks while many real world networks such as social and biological networks exhibit varying topology

In the last decade, Light Detection and Ranging (LIDAR) became a leading technology of detailed and reliable 3D environment perception. This paper gives an overview of the wide applicability of LIDAR sensors from the perspective of signal processing for autonomous driving, including dynamic and static scene analysis, mapping, situation awareness which functions significantly point beyond the role of

Frequency estimation of multiple complex and real sinusoids in noise has attracted wide attention in many fields. In this paper, two frequency domain parametric methods are proposed to estimate the frequencies of multiple complex and real sinusoids accurately. The first method for complex sinusoids adopts Discrete Fourier Transform (DFT) and interpolation algorithm to obtain the coarsely estimated

A comprehensive literature review on vessel behaviour pattern recognition in maritime and littoral environments, spanning a period of three decades, is presented. A vast majority of research focuses on anomalous vessel behaviour detection from Automated Identification System (AIS) data, using artificial intelligence (AI), Bayesian networks and machine learning based methods. AIS is a cooperative system

Cross-technology interference sources poses a great challenge for improving throughputs of wireless local area networks (WLAN) and wireless interference signal recognition (WISR) can provide a precondition for mitigating this problem. The quadruple generative adversarial network (QGAN) has shown its prevailing performance for specific emitter identification (SEI). In this paper, an enhanced collaborative

Feature selection has attracted widespread attention with the massive growth of high-dimensional data. In recent years, all kinds of unsupervised feature selection methods have been presented. However, most of these methods can not fully explore the local geometric structure of the original data, which has been proven very important in unsupervised feature selection. To tackle this problem, we present

Interleaving techniques are used to improve the probability of error correction in communication systems. In a non-cooperative context, interleaver parameters must be determined first so that the received data can be decoded into relevant information. This paper proposes blind interleaver parameter estimation method based on the Hamming weight distribution. Conventional methods based on rank distributions

Time delay estimation (TDE) has been an essential topic in both theoretical research and engineering practice. The effective models and solutions related to this work have been offered by pioneers, and preferable results are achieved. Nevertheless, in the environment of co-channel interference and impulsive noise, the traditional methods are degraded or even be unavailable. To solve these problems

In existing methods of ISAR imaging with MMV (Multiple Measurement Vector) SBL (Sparse Bayesian Learning), the HRRP is always interpolated radially to realize the column-to-column correspondence between HRRP matrix and scattering coefficient matrix, then scattering coefficients are estimated with MMV SBL algorithm. In order to enhance the ability to suppress noise and eliminate stripe interference

Some Siamese-based trackers use temporal context prior as structural constraint to suppress background distractors. However, due to the lack of contour recognition, it is difficult to obtain a better performance. In order to address this issue, we propose a structural pixel-wise target attention strategy for robust object tracking with memory model. Firstly, a pixel-wise target attention model is constructed

This paper presents an adaptive algorithm for unbiased estimation of autoregressive Rayleigh flat fading parameters in OFDM systems. To this end, a variable leaky steepest descent algorithm is proposed. The authors use a variable leak parameter in the algorithm to remove the noise induced bias from the autoregressive estimates. Theoretical performance analyses of the proposed method are conducted.

Molecular Communications (MC) is a bio-inspired communication technique that uses molecules to transfer information among bio-nano devices. In this paper, we focus on the detection problem for biological MC receivers employing ligand receptors to infer the transmitted messages encoded into the concentration of molecules, i.e., ligands. In practice, receptors are not ideally selective against target

In this paper, an efficient and practical solution to cope with random linear network coding (RLNC) drawbacks and maximize the system throughput is proposed. No header overheads and no retransmissions are required as a result of the introduction of a unique codebook at the nodes in charge of RLNC coding and decoding. The codebook contains the seeds that allow for the pseudo-random generation of full-rank

The emerging orthogonal time frequency space (OTFS) modulation is demonstrated to offer reliable communication performance advantages over orthogonal frequency division multiplexing (OFDM) in doubly-dispersive fading channel. However, the existing embedded pilot-aided method to estimate channel impulse response (CIR) requires enormous spectral overhead to avoid the contamination of pilot symbols. In

This article is dedicated to the estimation of the parameters of a linear-circular regression model. For this model, the response is circular and defined between −π and π, the predictor is linear and several sensors provide noisy observations of the response. In our approach, the noise is assumed to be distributed according to a von Mises distribution with a concentration parameter that models the

In this paper, we investigate low probability interception (LPI) in passive phased array radars. Power control and transmit beamforming (BF) are used to minimize the received power by the interceptor. Meanwhile, desired target detection performances and the limited power budget of radar are guaranteed. The LPI problem is solved analytically and some theorems are derived for the design of optimum BF

The multi-channel sampling theorem has flourished as one of the nicest alternatives to the classical Shanon's sampling theorem which relies on non-uniform or multi-channel data acquisition. Although, a primary attempt to study the multi-channel sampling theorem for the multi-dimensional linear canonical transform (LCT) was made by D. Wei and Y. Li (2014) [16], however, it lacks the inherent multi-dimensional

This paper proposes a multimodal fusion emotion recognition method based on Dempster-Shafer evidence theory, which includes electroencephalogram (EEG) and electrocardiogram (ECG). For EEG, we use the SVM classifier to classify features, and for ECG, we establish the corresponding Bi-directional Long Short-Term Memory network emotion recognition structure, which is fused with EEG classification results

This paper addresses the filtering problem for a class of discrete-time cyber-physical system (CPS) in simultaneous presence of physical attack, denial of service attacks (DoS), false data injection (FDI) attacks and randomly occurring nonlinearities (RONs). The malicious attacks can be simultaneously launched at the physical and cyber space to assault/disturb the system's state or block the measurement

Analog-to-digital converter (ADC) is an indispensable application for wireless communication systems, but the model of the quantization error induced by ADC is still an open interdisciplinary problem. This paper proposes a general framework of quantization error model for multiple-input multiple-output (MIMO) system employing orthogonal frequency-division multiplexing (OFDM) with medium-precision ADCs

The recent research activities on molecular communications systems highlighted impressive potentials for realizing new services in many fields. They include biomedical systems, nanotechnologies, food production and many others. Since the nature of such areas may be extremely different, in terms of geometrical scale, information delivery media, and related technologies, the proposed molecular communication

According to the Heisenberg uncertainty principle, an analysis window with a high time resolution in time domain will result in a low frequency resolution in frequency domain, and vice versa. To obtain the Gabor spectrum with high time-frequency resolution and concentration, weighted multiwindow discrete Gabor transform (M-DGT) using weights and the biorthogonal analysis method for analyzing long (or

This article introduces the Discrete Path Transform (DPT). Designed to serve as a new tool for handcraft feature extraction (FE), it improves the elementary analysis provided by signal energy (E) and enhances the humble spectral investigation granted by zero-crossing rates (ZCRs). C/C++ source-codes to realize both the DPT direct and inverse (IDPT) forms are presented together with a few hypothetical

This survey paper focuses on the estimation schemes in molecular communication (MC) systems. The existing studies in estimation schemes can be divided into parameter estimation (e.g., distance, diffusion coefficient, and flow velocity) and channel estimation. In this paper, we present, for the first time, a comprehensive survey on i) distance estimation, since distance is the most widely estimated

This paper proposes a marginal multi-object Bayesian filter with multiple hypotheses to track multiple objects in the presence of object appearing and object disappearing, missed detection and clutter. This filter delivers the probability of existence and probability density function of each object. A mathematical model for searching K-best hypotheses is set up by the maximization of the generalized

Diffusive molecular communications (DiMC) have recently gained attention as a candidate for nano- to micro- and macro-scale communications due to its simplicity and energy efficiency. As signal propagation is solely enabled by Brownian motion mechanics, DiMC faces severe inter-symbol interference (ISI), which limits reliable and high data-rate communications. Herein, recent literature on DiMC performance

This paper is concerned with the multitarget tracking over decentralized sensor networks where the network can potentially be compromised by malicious cyber attacks. We consider the hybrid cyber attacks, including denial of service (DoS), false data injection (FDI), and extra packet injection (EPI) attack. We first establish the feature model of DoS, FDI and EPI attacks for decentralized multitarget

In this paper, two low computational complexity accurate array response control algorithms for large-scale antenna array are presented. The first proposed algorithm is an Improved Weight vector ORthogonal Decomposition (I-WORD) approach. We extend the WORD method by selecting the non-negative coefficient as the ultimate solution, and thus the ultimate weight vector will be in an exact form. Therefore

Continuous wave telemetry is one of the critical downhole-to-surface transmission techniques of downhole information for logging while drilling (LWD). This paper aims to present a highly effective modulation technique for a continuous wave telemetry called Continuous Phase-Frequency Keying (CPFK) and an adaptive coherent detection method for the CPFK signal. The modulation equation of the CPFK signal

Relay networks typically experience channel-state-information impairments in practice, which has been known to severely impact their effectiveness. Despite their practical importance, research on CSI impairments has appeared to be scarce in the existing literature. In this work, assuming that relays operate under independent-and-identically-distributed Rayleigh fading, this paper studies the impact

Basis functions of the Discrete Hermite transform (DHT) can be formed as the set of eigenvectors of a symmetric tridiagonal matrix which commutes with the centered discrete Fourier transform matrix. In this paper, we consider the optimization of the associated time-axis scaling factor, which is of crucial importance in the DHT-based applications. The parameter optimization is performed to enhance the

Fault prediction technology provides a way to reduce the loss caused by equipment failure. Currently, many efforts of failure prediction pay more attention to the fault trend and the remaining useful life. This paper devotes to predicting a specific failure mode of device in the future. We propose a two-step prediction method with two sub-models to predict the fault mode. The first model, named regression

Since functional Magnetic Resonance Imaging (fMRI) signals are a group of sparse signals, and its autocorrelation matrix contains limited information, it is difficult to accurately locate the brain activation area directly using traditional blind separation algorithms. For the issue, this paper proposes a method with inverse-sparse transform and second order blind identification (SOBI) for the separation

Empirical wavelet transform (EWT) can successfully decompose a smooth or noise-free simulated signal into several components. This method has encountered difficulties in processing simulated signals containing noise and in applications. In order to improve the shortcomings of EWT and expand its application, this paper proposes a variable spectral segmentation EWT (VEWT) associated with the trend of

In this paper, a novel approach is presented to estimate the metric scale (MSC) and roll and pitch angles of a platform by using distance sensors in a monocular visual odometry setup. A state-of-the-art visual odometry algorithm Semi-Direct Visual Odometry (SVO) [1] is used to obtain sparse three dimensional (3D) point cloud which is then matched with the measurements obtained from the distance sensors

The design of filter banks, which is a frequently used operator for many practical applications, has been widely reported in the literature. The requirements of using extensive mathematical manipulations for finding computationally efficient structures of filter banks have imposed severe difficulties for those who lack sufficient mathematical background. This paper is to report procedures of deriving

A bilinear interpolation technique is proposed for flexible representations of quantum images (FRQIs). In this process, several quantum modules were developed, including assignment, increment, and quarter modules, for use in an interpolation circuit. The network structure of these circuits, capable of both up-sampling and down-sampling FRQIs, was investigated as part of the study. Additionally, the

This paper considers the waveform design for colocated MIMO radar to improve target detectability embedded in signal-dependent interferences, and maximize the SINR (signal-to-interference-plus-noise ratio). Due to constant modulus constraint, the problem is indeed non-convex and NP-hard. To address the challenge of this intractable problem, we propose a novel optimization framework for solving the

This work proposes a new and efficient sparse representation-based spatial compression of video signals integrated with a hyper-chaotic DNA coding-based encryption module that provides higher security. The betterment of compression efficiency is achieved by introducing sparse coding on the video frames, and higher security is obtained by applying 5D hyper-chaotic DNA coding on the sparse coded frames

Smart wearable devices have become more and more popular in our daily life due to their unique power of “wearing-while-using.” However, requirements of light weight and compact size lead to limited on-device resources in most wearable products, which hamper the development of wearable technology. Edge computing provides an opportunity for wearable devices to access more resources without violating

Light Field Image (LFI) can simultaneously record the intensity and direction information of light rays, and provide users with strong immersion experience. However, heterogeneous artifacts may be introduced during LFI processing, which results in degradation of the perceptual quality of LFI. To evaluate the LFI quality effectively, a novel blind light field image quality assessment method by analyzing

Flexible organic photodetectors that are lightweight, conformable, cost-effective, and compatible with large-scale processing techniques will meet the demands of next-generation wearable devices in the era of Internet of Things (IoT). Recent advances in various flexible organic photodetectors and their accompanied signal processing circuits have greatly enriched the application scenarios of wearable

Chemical reactions and diffusion are two basic mechanisms governing the dynamics of molecules in a fluid. As such, they play a critical role in molecular communication for channel modeling, design of detection rules, implementation of molecular circuits for computation, and modeling interactions with external biochemical systems. For finite numbers of information-carrying molecules, stochastic models

Facial expression recognition has become an increasingly important research topic in pattern recognition and affective computing. Most of facial expression recognition methods assume that the training and testing data come from the same corpus. However, in practical situations, this assumption does not hold, in which the data are often collected from different scenarios, e.g., different races, environments

Semi-continuous data comes from a distribution that is a mixture of the point mass at zero and a continuous distribution with support on the positive real line. Such data appear in several real-life situations like blind signal separation problems, modeling of loss data in finance and insurance, sales of consumer goods, daily precipitation data, to name a few. In this paper, we present a novel algorithm

As an indispensable part of array signal processing, direction-of-arrival (DOA) estimation has been well investigated over the past few decades, and many excellent DOA estimation methods have been proposed. In this paper, a receiving domain covariance vector (RxCV) based unitary SBL algorithm is proposed for the off-grid DOA estimation of monostatic multiple-input multiple-output (MIMO) radar in unknown

Cancellable biometrics is the art of generating distorted or encrypted templates of original biometric templates. The evolution of cancellable biometrics is attributed to the advanced hacking technologies that can capture the original stored biometrics from databases. One of the solutions for this problem is to store cancellable biometric templates in the database rather than the original ones. This

Interest is growing in the application of the spatial location information from weather scenario to the monitoring of meteorological signal for airborne weather radar system. Here, a new algorithm utilizes the differences between ground clutter and meteorological signal in terms of the spatial location in elevation dimension to achieve weather signal detection (WSD). Specifically, weather signal submerged

Our efforts towards developing an automatic speaker verification (ASV) system for child speakers are presented in this paper. For the majority of the languages, children's speech data for training the ASV system is either unavailable (zero-resource) or very limited (low-resource). Under low- and zero-resource conditions, developing an ASV system becomes a very challenging problem. To overcome this

Traditional phase retrieval methods for sparse signals are not able to achieve optimal performance when dealing with special-structured signals such as block-sparse signals. In this paper, we focus on the phase retrieval for block k-sparse signal x∈CN, with uniform block size d. Taking advantage of the block-sparse property, an algorithm, called block compressed phase retrieval via lifting (BCPRL)

Advances in machine learning technology have enabled real-time extraction of semantic information in signals which can revolutionize signal processing techniques and improve their performance significantly for the next generation of applications. With the objective of a concrete representation and efficient processing of the semantic information, we propose and demonstrate a formal graph-based semantic

In this paper, we discuss the state of radio frequency (RF) coexistence and how it benefits from dynamic spectrum sensing. We categorize coexistence of radar and communications in terms of their cooperation and non-cooperation in using the spectrum as well as their roles as primary, secondary, and dual users of the frequency bands. We describe the ways the radar can alter its parameters in response

Sequences with low autocorrelation sidelobes has applications in various fields like wireless communications, radar, sonar, cryptography to name a few. In this paper, we propose an approach to construct sequences, in particular unimodular sequences, by directly minimizing the peak sidelobe level (PSL) metric. The underlying optimization problem involved is a minimax problem which is in general difficult

The Hilbert transform of mono- and multicomponent periodically non-stationary random signals (PNRSs), the carrier harmonics of which are narrow-band low-frequency modulated, are considered here. The relations for the auto- and cross-covariance and cross-spectral functions of a PNRS and its Hilbert transform are analyzed and the conditions for stationarity of the analytical signal are obtained. The

The distribution of aircraft dynamic radar cross section (RCS) varies at different course short-cuts and heights and can behave as a bimodal shape. Classical models, such as the Weibull distribution, the chi-square distribution, and lognormal distribution, fit poorly with bimodal RCS distributions and are unable to accurately describe the statistical characteristics of aircraft dynamic RCS. In order

The robust watermarking method embeds the information in the image to protect the copyright. The embedding process will destroy the original image and cannot be effectively applied to the images used in the medicine and military with high integrity demand. A robust zero-watermarking algorithm for lossless copyright protection of color images without changing the original image was proposed in this

A two-stage technique for estimating hyperbolic frequency modulated (HFM) signal parameters is proposed. In the first stage, coarse parameter estimations are performed through a regression of the group delay estimate obtained from an unwrapped spectrum phase due to its robustness to noise. In the second stage, the coarse estimates are refined by a combination of the Newton-Raphson strategy and O'Shea