In adaptive filters, variable step-size-based algorithms have demonstrated better performance than conventional least mean square (LMS) and normalized LMS (NLMS) algorithms in terms of convergence speed, mean square error (MSE), and signal-to-noise ratio (SNR) improvement. Recently, adaptive filters have been recommended to be implemented on field programmable gate array (FPGA) devices due to their

Signal modeling is an important technique in many engineering applications. This paper is concerned about signal modeling problem for the sine multi-frequency signals or periodic signals. In terms of different characteristics between the signal output and the signal parameters, a separable modeling scheme is presented for estimating the signal parameters. In order to seize the real-time information

This paper aims to propose an effective steerable directional Laplacian regularizer for image denoising. A steerable inhomogeneous directional Laplacian associated with an efficient contextual indicator is presented and taken as the diffusion flux to formulate the desired steerable directional Laplacian regularizer. With the contextual indicator for contextual discontinuities, the steerable directional

An optimized color image watermarking algorithm with stationary wavelet transform and singular value decomposition has been proposed in this work. The algorithm uses two watermarks to address the issues of copyright protection and tamper localization. A gray-scale image watermark is embedded in the transform domain of the green plane of the cover image to address the issue of copyright protection.

Approximate computing is a striking approach to design area-efficient low-power datapath units for fault buoyant applications. This brief presents the design of a novel 4: 2 approximate compressor that generates no error in the carry signal. The proposed compressor is employed for partial product (PP) compression in two variants of Dadda multiplier to see its effectiveness in error-resilient image

\(\varDelta \varSigma \) analog-to-digital converters (ADCs) are largely used in sensor acquisition applications. In the last few years, standalone \(\varDelta \varSigma \) modulators have become increasingly available as off-the-shelf parts. To build a complete ADC, a standalone modulator has to be paired with some advanced elaboration unit, such as a field programmable gate array (FPGA) or a digital

We address the problem of signal denoising and pattern recognition in processing batch-mode time-series data by combining linear time-invariant filters, orthogonal multiresolution representations, and sparsity-based methods. We propose a novel approach to designing higher-order zero-phase low-pass, high-pass, and band-pass infinite impulse response filters as matrices, using spectral transformation

A method for assigning characteristic functions on rational functions is presented herein. In systems with rational characteristic loci, input–output decoupling and commutative compensator design are possible. In this method, unlike previous research, which used the approximation method in a specific frequency range, a perturbation is created in the transfer function such that a new transfer function

In this paper, a new array configuration termed as Spread Orthogonal Loop and Dipole (SOLD) array is presented for estimating direction and polarization parameters of multiple incident signals. In the SOLD array configuration, the spacings of any two adjacent SOLD antennas are set to be mutual primes with respect to a half-wavelength. Moreover, the loop is separated far away from the dipole within

This paper introduces a simulated grounded inductor (SGI) circuit realization based on two terminal active devices, namely negative impedance converters. The proposed SGI contains a minimum number of passive components when compared to its two terminal active device-based realization counterparts in the literature. It includes a grounded capacitor that is an advantage in integrated circuit process

In this paper, we propose a novel low-complexity scheme to extract cyclic features of wideband signals from sub-Nyquist samples as Nyquist rates push contemporary analog-to-digital converters to their performance limits. Due to the sparse spectrum occupancy in wideband, sub-Nyquist sampling is performed and cyclostationary feature extraction is achieved at baseband to identify the modulation scheme

This paper proposes a new approach to investigate the problem of designing sampled-data controller for master–slave synchronization of chaotic Lur’e systems with time delay. Compared with existing methods, this method can make full use of the information of actual sampling pattern. To reflect more realistic the information on both the intervals e(t) to \(e(t_{k})\) and e(t) to \(e(t_{k+1})\), a novel

Watermarking of digital images is a well-known technique that is widely used for securing image contents. A successful watermarking method must be accurate, reversible, resilient, and robust against various attacks. In this paper, we propose a reversible and robust color image watermarking method. A new set of multi-channel fractional-order polar harmonic transforms and their geometric invariants have

The problem of 3D digital object invariability is encountered in image processing, especially in pattern classification/recognition. The 3D object should be correctly recognized regardless of its particular position and orientation in the scene. This paper proposes a new method to extract 3D Charlier moment invariants to translation and scaling (3DCMITS). These descriptors are extracted directly from

The finite-rate-of-innovation (FRI) sampling frame has drawn a great deal of attention in many applications. In this paper, a novel sub-Nyquist FRI-based sampling and reconstruction method in linear canonical transform (LCT) domain is proposed. First, a new, compact-support sampling kernel is designed to acquire sub-Nyquist samples in time domain, which can be viewed as anti-aliasing prefilter in LCT

Direction of arrival (DOA) estimation has paramount importance in array signal processing tasks. A practical issue regarding DOA estimation is the uncertainty in gain/phase of some of the sensor elements. In this paper, we focus on the 2-dimensional DOA (2D-DOA) estimation in the presence of gain/phase uncertainty. We propose a grid-based modeling for the 2D-DOA estimation of the uniform rectangular

Direct acoustic feature-based speaking rate estimation is useful in applications including pronunciation assessment, dysarthria detection and automatic speech recognition. Most of the existing works on speaking rate estimation have steps which are heuristically designed. In contrast to the existing works, in this work a data-driven approach with convolutional neural network-bidirectional long short-term

This paper proposes a novel method of image enhancement via energy curve equalization (ECE). Histogram equalization (HE) appears to be the most straightforward method for image contrast enhancement. Many modifications are already recommended to overcome the confines of HE. The computation of the histogram does not consider the spatial correlations among the surrounding pixels. The current method utilizes

This paper presents a modified minimal realization technique to reduce single input single output (SISO) systems from higher-order SISO systems. The reduction process is based on restructuring the Hankel matrix, which consists of two major elements, i.e., Time Moments and Markov parameters. The system transformation is executed to reduce the order of the system by maintaining the desired system properties

In this paper, speech enhancement is carried out using a modified nonlocal means adaptive filter, and an FPGA prototype is proposed for its implementation. Nonlocal means (NLM) adaptive filtering has been a widely used approach for denoising image and electrocardiogram signals. The temporal and spectral characteristics of the speech signal vary with time. Consequently, NLM filtering is ineffective

This paper presents an improved 8 × 8-bit Booth multiplier with reduced power, delay and area. The major operations that consume power and are responsible for larger critical path delays in Booth multiplication are partial product array generation (PPAG), partial product array compression (PPAC) and partial product array addition (PPAA), for the generation of the final product. So, in our proposed

In this paper, we discuss the problem of model order reduction for positive real systems based on balancing methods. The mixed gramian balanced truncation (MGBT) method, which is a modification of the positive real balanced truncation (PRBT) method, focuses on solving one Lyapunov equation and one Riccati equation resulting in less computational effort compared to PRBT requiring solving two Riccati

Approximate computing is gaining grip as a computing paradigm for computer vision, data analytics, and image/signal processing applications. In the era of real-time applications, approximate computing plays a significant role. In many computers including digital signal processors (DSP) and a microprocessor, adders are the main element for the implementation of signal processing applications and digital

Sinusoidal model and chirp model are the two fundamental models in digital signal processing. Recently, a chirp-like model was introduced by Grover et al. (International conference on computing, power and communication technologies, IEEE, pp. 1095–1100, 2018). A chirp-like model is a generalization of a sinusoidal model and provides an alternative to a chirp model. We derive, in this paper, the asymptotic

An on-chip nanopower RC relaxation oscillator is developed in a 180-nm standard CMOS process, consuming 300 nW while running at 10 kHz. Employing a frequency compensation scheme that reduces the frequency drift introduced by comparator offset and delay, the proposed oscillator achieves a significant low temperature coefficient. Furthermore, a supply regulation structure is used to reduce the frequency

Speech emotional content estimation is still a challenge for building robust human–machine interaction systems. Accuracy of emotion estimation depends upon the corpus used for training and the acoustic features employed for modelling the speech signal. Generally, emotion estimation is computationally expensive, and hence, there is a need of developing alternative techniques. In this paper, a low complexity

In this work, we propose a 2\(^7\)-1, 20-Gb/s, low-power, charge-steering, half-rate pseudorandom bit sequence (PRBS) generator in 1.2 V, 65 nm CMOS. At the target data rate, the proposed charge-steering implementation has the lowest power consumption of 0.2 mW/Gb/s compared to the current-mode PRBS generator implementations, thanks to the discrete nature of the charge-steering latch circuit topology

In this paper, we propose a low-complexity and high-speed VLSI architecture design methodology for complex square root computation using COordinate Rotation DIgital Computer (CORDIC). The proposed methodology is independent of angle computation in the CORDIC unlike the state-of-the-art methodologies. The proposed methodology is modelled in VHDL and synthesized under the TSMC 45-nm CMOS technology @

The fractional Fourier transform (FrFT) is a generalization of the usual Fourier transform. The aim of this paper is to show the compression of sound signal in FrFT domain and to prove the qualitative and quantitative uncertainty principles for the FrFT. The first of these results consists the Hardy’s and an \(L^p-L^q\) version of Miyachi’s theorems for the FrFT, which estimates of decay of two fractional

Many classic chirp signal processing algorithms may show significant performance degradation when the signal-to-noise ratio (SNR) is low. To address this problem, this paper proposes a pre-filtering method in time-domain based on deep learning. Different from traditional signal filtering methods, the proposed denoising convolutional neural network (DCNN) is trained to recover the pure signal from the

This article presents a high-performance hybrid full adder (HPHFA) designed with static CMOS logic and pass transistor logic to achieve better power delay product (PDP). The circuit was implemented using cadence virtuoso tool on gpdk 90 nm and 45 nm CMOS process technologies. Further, the structure has been extended to 32 bits to test the performance of HPHFA in higher-order circuitry. The proposed

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

Acoustical properties of snoring signal have been widely studied as a potentially cost-effective and reliable alternative to diagnosing obstructive sleep apnea hypopnea syndrome, with a common recognition that the diagnostic accuracy depends heavily on the snoring signal quality. In the paper, generalized subspace noise reduction based on noise covariance matrix estimate is proposed. The noise covariance

In this paper, we present an approach to the reconstruction of signals exhibiting sparsity in a transformation domain, having some heavily disturbed samples. This sparsity-driven signal recovery exploits a carefully suited random sampling consensus (RANSAC) methodology for the selection of a subset of inlier samples. To this aim, two fundamental properties are used: A signal sample represents a linear

Electroencephalogram (EEG) is a biomedical technique for capturing the human brain’s electrical information to process its activities and actions. EEG is one of the main methods commonly used in neuroscience, from clinical analysis to the design of brain–computer interfaces. The first one of the many challenges in an EEG system design regards the ultra-low amplitude of signals (i.e., of the order of

This paper investigates the controllability and reachability of periodically time-variant mixed-valued logical control networks (PTMLCNs). The PTMLCN considered in this paper consists of several mixed-valued logical control networks with periodically switching signals, which circulates among different mixed-valued logical control networks. First, a PTMLCN is transformed into a discrete dynamic system

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

This paper presents a new estimation technique for linear time-invariant (LTI) systems with bounded additional nonlinearities and/or disturbances, measurement noises, and initial states. A new direct methodology is developed to design an estimator optimizing the maximum estimation error of the system state or its linear function in a prefixed time interval. For some mechanical systems, both the parameters

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