A required step to realize blind source separation of a signal is to determine the number of sources building up the mixture. Generally, the assumption of equal number of sources and mixtures is imposed which becomes invalid in single-channel mixtures. Therefore, in order to apply conventional solutions, a single-channel mixture signal can be converted into a pseudo-multi-channel signal. The empirical

We consider the design of constant-modulus waveforms for wideband multiple-input multiple-output radar. The aim is to match a desired transmit beampattern. To tackle the non-convex design problem, we develop an iterative algorithm, which is based on cyclic optimization and majorization–minimization. We prove that the sequence of the objective values of the proposed algorithm has guaranteed convergence

In recent years, reversible circuits have attracted the attention of many researchers. Their applications include the design of low-power digital circuits, the design of computational circuits in quantum computers and DNA-based calculations. In this paper, an effective 5 × 5 reversible block, called new block (NB), is first proposed, and then, using the proposed reversible block, a novel reversible

A new source coding is proposed for secure and robust speech communications. The method is based on the combination of compressed sensing and split-multistage vector quantization. The proposed codec is integrated in an end-to-end communication system, and its performance is investigated in real mobile communication conditions. Channel compensation techniques are considered to mitigate the Rayleigh

We study the node-specific parameter estimation problem, where agents in a network collaborate to obtain the different but overlapping vectors of parameters, which can be of local interest, common interest to a subset of agents, and global interest to the whole network. We assume that all the regressors and the measurements are corrupted by additive noise. For these settings, a bias-compensation r

A novel energy-saving and area-efficient tri-level switching scheme is proposed for successive approximation register analog-to-digital converters (SAR ADCs). Different from most published tri-level switching schemes, a new third reference voltage Vaq which equals to 1/4 Vref is applied to the proposed scheme. And benefiting from Vaq, the proposed scheme achieves 87.5% capacitor area reduction over

In this paper, we consider the problem of sparse signal recovery using a learned dictionary in multiple measurement vectors (MMVs) case. Employing deep neural networks, we provide two new greedy algorithms to solve sparse MMV problems. In the first algorithm, we create a stacked vector of measurement matrix columns and a new measurement matrix, which can be assumed as the Kronecker product of the primary

Sparse component analysis techniques have been successfully applied to the separation of speech sources. This paper presents an efficient algorithm based on the matching pursuit approach to deal with multichannel records. The proposed algorithm explicitly employs spatial constraints among different channels to express mixed signals as linear combinations of delayed components selected from an overcomplete

Nowadays, advances in technology have led to the expansion of the use and exchange of digital data, which places great importance on the security of these data. The protection of exchanging messages, passwords of email accounts, bank accounts and many others requires the security of textual data. Likewise, the security of medical images, personal images, captures from military satellites, plans to

An impedance read-out circuit with high accuracy implemented using a TSMC 0.18 um mixed-signal CMOS process for BIA-type (bio-electrical impedance analysis) sensors to detect biomarkers is proposed in this investigation. In addition to proposing the impedance estimation circuit, the associated analytic proof is also disclosed. Using a high-order approximation model and high noise rejection capability

A mixed-method for the order abatement of large-scale linear dynamic systems (LSLDSs) into desired low order systems is proposed. The denominator of the abated system (AS) is obtained by the renovated pole clustering technique, while the numerator is obtained by Cauer second form technique. The AS is stable if the original system (OS) is stable and retains all the essential time and frequency response

The special affine Fourier transform (SAFT) generalizes a number of well known unitary transformations, signal processing transformations and optics related mathematical operations. For example, Fourier transform, fractional Fourier transform, linear canonical transform, etc. The short-time special affine Fourier transform (STSAFT) is a novel time-frequency analysis tool, which solve the limitation

This paper studies H∞ control of Markovian jump linear singularly perturbed systems (MJLSPSs). A sufficient condition in terms of linear matrix inequalities (LMIs), different from ones in previous existing works, is given for designing H∞ control to overcome the difficulties of solving either Riccati equations or nonlinear matrix inequalities. Then, the jump H∞ controller can be obtained effectively

The widely linear model has attracted much attention due to its good features for non-circular adaptive signal processing in recent years. In this paper, a sparsity-induced augmented complex-valued NLMS algorithm is proposed to promote the performance of the adaptive filter for estimating sparse systems, which is established by incorporating the \(l_0\)-norm regularization into the squared error normalized

Image denoising is a fundamental but difficult task in image processing. Recovering a clean version from an image corrupted by mixed Gaussian and impulse noise is still challenging. The weighted sparse representation (WSR) method has been applied to deal with mixed noise and has achieved good performance. However, the WSR model presents an obvious disadvantage due to oversmoothing of the texture regions

In this paper, an inverter-based true time delay (TTD) cell for timed array receivers is proposed. The proposed TTD cell is designed in TSMC 0.18 µm CMOS technology for multi-GHz operations. The delay cell is made from an all-pass filter by Padé approximation. The first-order all-pass filter is built by combining a constant gain stage and a low pass stage based on the approximation. The constant gain

The leader-following issue for a class of nonlinearly coupled complex networks with multiple time-varying delays was investigated in this study. A distributed controller was introduced for realizing the exponential synchronization of the complex network with different delay scales that are known in advance. The Lyapunov stability theorem and mathematical induction method were used to obtain delay-dependent

The cleft of the lip and palate (CLP) is a congenital disability affecting the craniofacial region and it impacts the speech production system. The current work focuses on the modification of misarticulations produced for unvoiced stop consonants in CLP speech. Three types of misarticulations are studied: glottal, palatal, and velar stop substitutions. The stop consonants are misarticulated due to

Based on local quaternion polar complex exponential transform (QPCET) and Cauchy–Rayleigh distribution, we propose a statistical color image watermarking scheme in this paper, which can achieve the trade-off among imperceptibility, robustness and data payload. Our color image watermarking scheme consists of two parts, namely embedding and detecting. In the embedding process, we divide the color host

In cognitive radio context, the coding parameters are unknown at the receiver. The design of an intelligent receiver is essentially to identify these parameters from the received data blindly. In this paper, we are interested in the blind identification of binary linear block codes from received noisy data. In order to recognize the code length, the concept of the normalized column weight vector is

Automatic text localization in natural environments is the main element of many applications including self-driving cars, identifying vehicles, and providing scene information to visually impaired people. However, text in the natural and irregular scene has different degrees in orientations, shapes, and colors that make it difficult to detect. In this paper, an accurate multi-oriented scene text localization

Blind Source Separation (BSS) has always been an active research field within the signal processing community; it is used to reconstruct primary source signals from their observed mixtures. Independent Component Analysis has been and is still used to solve the BSS problem; however, it is based on the mutual independence of the original source signals. In this paper, we propose to use Copulas to model

Image enhancement by histogram equalization reduces the number of gray levels that lead to information loss and unnatural appearance. This paper aims to improve the contrast and preserve information and edge details by employing gradient-based joint histogram equalization. It is achieved by a multiscale-based dark pass filter, which gives the pixel’s edge information. A joint histogram is computed

Network pruning offers an opportunity to facilitate deploying convolutional neural networks (CNNs) on resource-limited embedded devices. Pruning more redundant network structures while ensuring network accuracy is challenging. Most existing CNN compression methods iteratively prune the “least important” filters and retrain the pruned network layer-by-layer, which may lead to a sub-optimal solution

This paper proposes a carbon nanotube FET (CNFET)-based ultra-low-power dual-\(V_{DD}\) ternary half adder (HA) circuit. The proposed design utilizes both the available ternary power supply voltages (\(V_{DD}\) & \(V_{DD}/2\)) and prevents direct path between the power supplies and ground, thus significantly reducing the power dissipation as compared to the conventional designs. The performance of

A new method for multiple sources localization is proposed to eliminate association ambiguity for near and far mixed field sources. A spatial source localization model in the modified polar representation was constructed without the prior knowledge needed if the source is near-field or far-field. The localization model for multiple sources was deduced by using all the possible permutation of the TDOA

Several phenomena encountered in nature are characterized by very localized events occurring randomly at given times. Random pulses are an appropriate modelling tool for such events. Usually, the impulses are hidden in the noise due to unwanted convolution. In some cases, the problem is more complex because of the short time lag between the pulses. Considering these problems, the resulting signal is

This research article proposes high-performance square-root carry select adder (SQRT CSLA) architectures with high speed, area and energy efficiency when compared to the existing SQRT CSLA architectures. The first proposed method uses an optimized design of binary to excess-1 converter (BEC)-based SQRT CSLA by incorporating a carry enable binary to excess-1 converter (CEBEC) design that exploits a

Phase rotator-based digital clock and data recovery (CDR) using multi-level bang-bang phase detector (ML-BBPD) and time to digital converter (TDC) is analyzed at system and circuit level. A model is proposed for calculating the quantization noise and bit error rate (BER), in order to evaluate the important parameters in CDR design. The jitter analysis is done based on the probability density function

This paper proposes a high-speed deterministic digital technique to calibrate the errors due to capacitance mismatch and finite op-amp gain. Unlike other calibration techniques, this technique requires neither forcing the inputs of the intermediate stages being calibrated to exact voltages, nor reducing the gains of each stage to avoid saturation of output digital codes. A 1.5 bits/stage, 10 stages

This paper investigates the analysis of critical path delay in various infinite impulse response (IIR) digital filter structure implementations. The critical path delay increases with the order of filter increasing in all conventional structures. So, it is needed to reduce the critical path delay for the faster realization of a digital filter in real-time processing. This paper proposed the rules for

In this paper, a novel Hybrid Deep Ensemble (HDE) is proposed for automatic speech disfluency classification on a sparse speech dataset. Categorizations of speech disfluencies for diagnosis of speech disorders have so long relied on sophisticated deep learning models. Such a task can be accomplished by a straightforward approach with high accuracy by the proposed model which is an optimal combination

This paper proposes the application of the Wiener–Hammerstein with feedback (WHFB) model as a digital pre-distortion (DPD) behavioural model for power amplifiers (PA) under load impedance mismatch, since more traditional models suffer performance degradation in this condition. Moreover, this paper proposes the use of the least absolute shrinkage and selection operator (LASSO) approach for the sparse

This work addresses stability of interfered digital filters with state-delay and saturation arithmetic. By utilizing a quadratic Lyapunov functional and properties of saturation overflow, a new condition is established to ensure stability of interfered digital filters under the influence of saturation arithmetic and state-delay. The criterion is capable of finding minimum \(H_\infty \) norm in the

An augmented joint domain localized technique for computationally efficient polarimetric space–time adaptive processing (pSTAP) is proposed. In the proposed method, the signal vector to be detected is first estimated by using a modified least square method, and then the clutter plus noise covariance matrix (CNCM) required by pSTAP is estimated by using a newly developed dimension-reduced (DR) scheme

Heterogeneous triangular network composed of resistors, capacitors and inductors gives a genuine electrical model for analyzing many engineering and physical problems. Here, we discuss various designs of RLC electrical circuits possessing a triangular topology. The theoretical formulation uses the WCIP technique. The proposed method rests on the definition of the incident and reflected waves from the

The distributed \(H_\infty \) state estimation of delayed sensor network is dealt with in this paper. To deeply reflect the time-delay phenomenon in the process of information fusion, a model containing state time-varying delay and different communication delays is set up. Afterwards, a fresh Lyapunov–Krasovskii functional (LKF) is given, which contains different kinds of time delays, delay-dependent

Data stream processors and accelerators, due to the outstanding energy performance, run on hardware more than any time in modern designs. The general model for these processors comprises massive shift register arrays with the largest share in energy dissipation and processing elements (PE). In this paper, a new gated flip-flop is designed and utilized in shift register arrays, to decrease power consumption

In this paper, we present a new two-stage speech enhancement approach, specially conceived to reduce musical and other random noises without requiring their localization in the time–frequency domain. The proposed method is motivated by two observations: (1) the random scattering nature of the energy peaks corresponding to the musical noise in the spectrogram of the processed speech; and (2) the existence

This paper proposes a novel method to reduce the order of prediction filter from 10 to 7 in Code Excited Linear Prediction (CELP) coding framework by the inclusion of psychoacoustic Mel scale into Linear Predictive Coding (Mel-LPC). Efficient quantization methods using 2-split Vector Quantization (VQ) for Mel-LPC obtained a reduction of 4 bits/frame and resulted in a total bit gain of 200 bps. A weighting

The reversible computation is the process of designing the architecture with reversible logic gates (RLG) and applicable for optical computing, digital signal processing, nanotechnologies and low-power circuits. In this study, integer wavelet transform (IWT) compression technique is applied to the input image to compress the pixel value. The utilization of the IWT is used to improve the quality of

The generalized variable step-size diffusion continuous mixed p-norm (GVSS-DCMPN) algorithm is proposed in this paper, which is derived based on the improved continuous mixed p-norm (CMPN) strategy. In detail, a linear function is designed for the CMPN strategy. The proposed GVSS-DCMPN algorithm capable of exploiting various error norms to obtain performance improvement in non-Gaussian noise environment

This paper presents a power-efficient successive-approximation register (SAR) analog-to-digital converter (ADC) with fast response reference buffer (RV-buffer). Several techniques are applied in the system design to improve the performance of the SAR ADC. A novel timing-redistribution SAR logic is proposed to balance the difference between required settling time for the most significant bit and the

Images recognition and classification require an extraction technique of feature vectors of these images. These vectors must be invariant to the three geometric transformations: rotation, translation and scaling. Several authors used the theory of orthogonal moments to extract the feature vectors of images. Jacobi moments are orthogonal moments, which have been widely applied in imaging and pattern

The use of 3D discrete orthogonal invariant moments as descriptors of images constitutes one of the hot topics in the field of 3D image analysis, especially in the recognition and classification of deformed objects, due to their high numerical precision and low computing complexity. The TSR (translation, scale and rotation) invariant functions of discrete orthogonal moments can be obtained by expressing

This paper is concerned with the problem of \(H_{\infty }\) control for a class of uncertain switched singular systems with time-varying state delays under asynchronous switching. The asynchronous phenomenon is caused by the choice of controller lagging behind the corresponding subsystem in practice. First, sufficient conditions by finding a novel piecewise Lyapunov–Krasovskii function combining with

In this paper, stochastic resonance effect on the optimal detection under Neyman–Pearson (NP) criterion is investigated for a general nonlinear system. To this end, a noise enhanced detection optimization problem for maximizing the probability of detection under a constant constraint on the probability of false-alarm is formulated, where an additive noise is added to the nonlinear system input and

A transformation for the 2D system is proposed to transform the original 2D systems into causal recursive separable denominator systems. 2D causal recursive separable denominator systems with minimal rank-decomposition can be written into two 1D systems for ease in the analysis and model order reduction.

Digital video technology has been increasingly needed in various fields, such as telecommunications, entertainment, medicine. Therefore, video compression is required. Motion estimation methods help in improving video compression efficiency by effectively removing the temporal redundancy between successive frames. Several block-based motion estimation (BME) algorithms are being suggested to reduce

The paper focuses on the finite-time \(H_{\infty }\) filtering (FTHF) design problem for a class of switched nonlinear systems (SNSs) via the T–S fuzzy model method. Different from the traditional FTHF design methods with time-triggered mechanism, a novel event-triggered scheme is proposed for SNSs, which takes full advantage of mixed switching signals. The information of system output and switching

Decomposition is an important tool that is used in many differential systems for solving real engineering problems and improving the stability of a system. It involves breaking down of high-order linear systems into lower-order commutative pairs. Commutativity plays an essential role in mathematics, and its applications are extended in physical science and engineering. This paper explicitly expresses

This paper addresses the problem of target localization using angle-of-arrival (AOA) measurements when the prior information of the AOA measurement noise variance is unavailable. At first, a maximum likelihood estimator (MLE) and the Cramér–Rao lower bound are derived for the case where the unknown noise variance is a function of the target-to-sensor distance. Then, a novel estimator is proposed to

This paper introduces a 10T single-ended SRAM cell with high stability and low static power. The read static noise margin is augmented by using a Schmitt-trigger inverter and decoupling the storage node from the read bitline by adding one transistor. Since writing “1” is difficult in single-ended SRAM cells, using proper capacitive coupling and also extra pMOS transistor as an access transistor mitigates

This paper proposes novel features for automated language and dialect identification that aim to improve discriminative power by ensuring that each element of the feature vector has a normalised contribution to inter-class variance. The method firstly computes inter- and intra-class frequency variance statistics and then distributes the overall spectral variance across spectral regions which are sized

This paper presents the optimization principle and law of classic scaling fractal fractance approximation circuits (FACs). The scaling extension of FACs with negative half-order operational performance can facilitate the design of scaling fractal FACs with arbitrary-order fractional operators. This report summarizes the operational performance and mathematics describing of typical scaling fractal FACs

We propose two graph matrix completion algorithms called GMCM-DL and GMCR-DL, by employing a new definition of Graph Total Variation for matrices based on the directed Laplacian Matrix. We show that these algorithms outperform their peers in terms of RMSEs for both cases of uniform and row observations.

Full adder cell is an important module in arithmetic and processing systems whose performance has a great impact on performance of the whole system. By continuous scaling of the MOS transistors, some challenges and problems appear such as high leakage dissipation for which emerging technologies have been studied as a solution. Carbon nanotube field effect transistor (CNFET) is one of the most potential

The leakage power, a.k.a. static power, increases in deep-submicron technologies due to short-channel effects. This article proposes a novel input-controlled leakage restrainer transistor (ICLRT)-based technique to reduce leakage power as well as the short-circuit power. The main idea is to place a PMOS and an NMOS ICLRT on top of the pull-up network (PUN) and at the bottom of the pull-down network

A novel technique is proposed for selecting iterative updates and step sizes based on adaptive function values to compensate for the slow convergence rate of artificial bee colony optimization (ABCO). On this basis, a blind source separation (BSS) algorithm is proposed based on adaptive ABCO and kurtosis, which does not impose any hypothetical requirements on the source signal. By using kurtosis as

To efficiently reduce the impact of the trading-off between the convergence rate and the quality of identifying a system, and also to improve the robustness of the algorithm against unknown sparsity levels, a Modified Absolute Weighted Input using Log function (MAWILOG) for NLMS algorithm is proposed. The essence of the proposed algorithm is to assign, individually, each coefficient of the adaptive