Some notes are presented on the paper “Finite-Time Control of Uncertain Fractional-Order Positive Impulsive Switched Systems with Mode-Dependent Average Dwell Time ” by Liu L. et al (Circuit Syst Signal Processing 37: 3739–3755, 2018). Fractional calculus has the memory property and this is relevant to the whole process from the initial value \(t_{0}\) to the current time t. However, this important

In this paper, a novel method is presented to analyze the amplitude modulated and frequency modulated (AM–FM) multicomponent signals using a combination of the variational mode decomposition (VMD) and the discrete energy separation algorithm (DESA). In the presented method, firstly, a multicomponent signal is decomposed using VMD method applied in an iterative way. In order to separate the monocomponent

In this paper, we would suggest a sparse adaptive filtering technique which is robust against Gaussian and non-Gaussian noises. To this goal, a linear combination of the least mean square and the least mean fourth loss functions has been considered as the fidelity term. Moreover, in order to promote the sparsity property of the underlying vector, we have added different sparsity-inducing penalty terms

The aim of this paper is to develop a productive numerical technique to deal with a class of time partial ideal AI control issues. The classical fuzzy inference methods cannot work to their full potential in such circumstances, because the given knowledge does not cover the entire problem domain. In addition, the requirements of fuzzy systems may change over time. The use of a static rule base may

A framework using semidefinite programming is proposed to enable the design of sigma delta modulator loop filters at the transfer function level. Both continuous-time and discrete-time, low-pass and band-pass designs are supported. For performance, we use the recently popularized Generalized Kalman–Yakubovič–Popov (GKYP) lemma to place constraints on the \(\mathcal {H}_\infty \) norm of the noise transfer

This paper investigates the stability of a class of fractional-order static neural networks. Two new Lyapunov functions with proper integral terms are constructed. These integrals with variable upper limit are convex functions. Based on the fractional-order Lyapunov direct method and some inequality skills, several novel stability sufficient conditions which ensure the global Mittag–Leffler stability

This paper presents a Gaussian-based distributed speech presence probability (DSPP) estimator which is applied in fully connected wireless acoustic sensor networks (WASNs). In WASNs, we are primarily interested in optimally utilizing all available information of recorded signals. In this work, under the Gaussian statistical assumption of signals, each node computes the DSPP using its own local signals

The recursive-least-squares (RLS) algorithm is one of the most representative adaptive filtering algorithms. \(\ell _1\)-norm full-recursive RLS has also been successfully applied to various sparsity-related areas. However, computing the autocorrelation matrix inverse in the \(\ell _1\)-norm full-recursive RLS generates numerical instability that results in divergence. In addition, the regularization

Facial recognition systems are critical components in numerous applications. They are used, for example, to prevent retail crime, unlock phones, find missing persons, protect law enforcement, and aid forensic investigations. In such real-world applications, the identification of facial information must be both quick and exact. The purpose of this study is to improve both the accuracy and speed of facial

Size reduction in complementary metal–oxide–semiconductor integrated circuits (ICs) is a challenge. Carbon nanotube field effect transistor (CNTFET) technology with advantages such as low power, high mobility, and ballistic transmissions is an alternative. Based on the standard 32 nm CNTFET technology, a new 23-transistor full adder cell is proposed with combining advantages of gate diffusion input

In this paper, a neurodynamic algorithm with finite-time convergence to solve \({L_{\mathrm{{1}}}}\)-minimization problem is proposed for sparse signal reconstruction which is based on projection neural network (PNN). Compared with the existing PNN, the proposed algorithm is combined with the sliding mode technique in control theory. Under certain conditions, the stability of the proposed algorithm

In this paper, we study the problem of passivity analysis of fractional-order neural networks (FONNs) with a time-varying delay. By using the Razumikhin fractional-order theorem, we first derive an improved sufficient criterion for asymptotic stability of FONNs with a bounded time-varying delay. Then, based on the proposed stability criterion and some auxiliary properties of fractional calculus, a

This paper presents the design and implementation of a low complexity and highly efficient configurable singular value decomposition (SVD) processor for 2 × 2, 4 × 4, 6 × 6, and 8 × 8 MIMO wireless communication systems. In order to minimize the area complexity while maintaining comparable throughput, novel data-processing sequences are proposed so that costly matrix multipliers are eliminated. Furthermore

This paper is concerned with the positive realness problem for second-order and high-order descriptor systems. First, without any linearization, necessary and sufficient conditions are established under which the second-order descriptor systems are strictly positive real and extended strictly positive real, respectively. Applying the relations between the positive realness and the optimal control theory

In this communication, two novel architectures of voltage mode analog divider circuit and square-root circuit using an operational transconductance amplifier (OTA) have been presented. The proposed divider circuit employs an OTA and two MOSFETs, while the square-root circuit requires one OTA along with one MOSFET. The proposed divider circuit can also be configured as inverse voltage function generator

In this paper, a new method for designing digital infinite impulse response filter with nearly linear-phase response is presented using fractional derivative constraints (FDC). The design problem is constructed as a phase optimization problem between the desired and designed phase response of a filter. In order to achieve the highly accurate passband (pb) response, phase response is fitted to desired

Body channel communications (BCCs) were investigated, to enhance requirements for low power and high-reconfiguration power within permitting technology of wireless measurement systems for wireless communication applications. Standard options for BCC are targeted totally toward channel modeling with a potency measuring technique, a transmission technique, and a wireless transceiver style. Wireless digital

This paper considers a single-input single-output linear dynamic system, whose input and output are corrupted by Gaussian white measurement noises with zero means and unknown variances; the parameter estimation of such a system is a typical errors-in-variables (EIV) system identification problem. This paper proposes the correlation function-based two-step identification methods for the EIV systems

In this paper, we propose a new image blind deblurring model, based on a novel low-rank prior. As the low-rank prior, we employ the weighted Schatten p-norm minimization (WSNM), which can represent both the sparsity and self-similarity of the image structure more accurately. In addition, the L0-regularized gradient prior is introduced into our model, to extract significant edges quickly and effectively

The generalised time–frequency transform (GTFT) is a powerful tool to analyse a large variety of frequency-modulated signals. However, it is not adequate to represent the variation of frequency over time for non-stationary signals. To solve this problem, short-time GTFT and short-time GTFT-based adaptive generalised fractional spectrogram (AGFS) are proposed. The AGFS is capable of providing a high

Partial-update (PU) algorithms offer reduced computational complexity to adaptive second-order Volterra filters (SOV) in nonlinear systems while retaining acceptable performance. In this paper, a new selective partial-update technique for the normalized LMS (NLMS) SOV algorithm is proposed, which requires lesser number of comparison operations per iteration than existing methods while providing close

The division datapath is undoubtedly the most complex operation in a wide range of digital signal processing applications, such as in adaptive filtering algorithms. This paper proposes an optimized and approximate integer divider hardware architecture, based on the Newton–Raphson algorithm combining both fixed-point dynamic range and truncation techniques, to speed up that operation. Adaptive filters

In this work, a switched capacitor-based successive approximation register (SAR) analog-to-digital converter (ADC) using a passive reference charge sharing and charge accumulation is proposed. For N-bit resolution, the fully differential version of this architecture needs only 6 capacitors, which is a significant improvement over conventional binary-weighted SAR ADC. The proposed SAR ADC is first modeled

Subband adaptive filtering algorithms can increase the convergence rate of system identification tasks when the input signal is colored. Recently, a new normalized subband adaptive filtering algorithm with sparse subfilters (NSAF-SF) has been proposed, whose main advantage is the lower computational complexity when compared to state-of-the-art subband approaches, while maintaining similar convergence

This work attempts to recognize emotions from human speech using prosodic information represented by variations in duration, energy, and fundamental frequency (\(F_{0}\)) values. For this, the speech signal is first automatically segmented into syllables. Prosodic features at the utterance (15 features) and syllable level (10 features) are extracted using the syllable boundaries and trained separately

This paper considers the adaptive event-triggered \(H_{\infty }\) control issue for Markov jump systems with generally uncertain transition rates and actuator faults. Compared with the conventional method, an adaptive event-triggered mechanism with a varying threshold is adopted to save the communication resources effectively. The general model of transition rates in Markov jump process includes completely

This paper presents a novel spike detection algorithm in nonstationary signals using a time–frequency (t–f) approach. The proposed algorithm exploits the direction of signal energy in the t–f domain to detect spikes in the presence of high-frequency nonstationary signals even at low signal-to-noise ratio. The performance of the proposed approach is evaluated using synthetic nonstationary signals, synthesized

This paper is concerned with finite-time and fixed-time synchronization of complex-valued recurrent neural networks with discontinuous activations and time-varying delays. First, by separating the complex-valued recurrent neural networks into real and imaginary parts, we get subsystems with real values covered by the framework of differential inclusions, and novel time-delays feedback controllers are

This paper proposes a finite-time observer-based controller for time-delay descriptor systems with time-varying disturbances, model uncertainties, and one-sided Lipschitz nonlinearities. For this purpose, first, a nonlinear descriptor observer is designed, and the observer error system is calculated. Then, the observer-based control law is proposed to provide the conditions for robust stabilization

This paper presents a capacitor calibration technique called median selection for improving the static and dynamic performance of the successive approximation register (SAR) analog-to-digital converter (ADC). Monte Carlo simulations in MATLAB are presented to demonstrate the effect of the proposed method. Simulation results show that for an 18-bit RC-hybrid SAR ADC with the mismatch of the unit capacitor

This paper deals with the Tobit Kalman filtering (TKF) process when the measurements are correlated and censored. The case of interval censoring, i.e., the case of measurements which belong to some interval with given censoring limits, is considered. Two improvements of the standard TKF process are proposed, in order to estimate the hidden state vectors. Firstly, the exact covariance matrix of the

A new model order reduction (MOR) method for large-scale time-delay differential algebra systems is proposed herein. The presented MOR algorithm is based on parametric moment matching and \(\varepsilon \)-embedding. By selecting an appropriate projection matrix, this process generates reduced-order models that preserve the structure of the original time-delay differential algebra system. Additionally

In multi-processor system-on-chips, on-chip interconnection plays a significant role. The type of on-chip architecture being used in an application decides the performance of that application. Hence, a quick and versatile network-on-Chip (NoC) simulator, particularly for the larger designs, is essential to explore and find the best suitable NoC configuration for individual applications. An FPGA-based

This paper presents a new approach for unsupervised segmentation and labeling of acoustically homogeneous segments from the speech signals. The virtual labels, thus obtained, are used to build unsupervised acoustic models in the absence of manual transcriptions. We refer to this approach as unsupervised speech signal-to-symbol transformation. This approach mainly involves three steps: (i) segmenting

This paper addresses the output-tracking control problem for a class of nonlinear sandwich systems with external disturbances and model uncertainties. Sandwich systems are a special class of nonlinear systems in the cascade structure, which are made up of several distinct subsystems while the non-smooth nonlinear functions are sandwiched among their separate subsystems. This paper concentrates on the

The short-time fractional Fourier transform (STFrFT) is beneficial for addressing non-stationary signals in many application settings. However, the STFrFT algorithm fails to obtain a high time–frequency (TF) concentration because of the uncertainty principle. To resolve these problems, we introduce a new algorithm that is referred to as the SSTFrFT, which is a combination of the synchroextracting transform

This paper presents a novel low complex configuration methodology by deploying a directed minimal spanning tree (DMST) algorithm for designing digital multiplierless finite impulse response filter. This method utilizes the shift inclusive differential coefficient and common sub-expression elimination (CSE) technique to minimize the multiple constant multiplications using steepest decent approach. The

Simple and integrable MOS-only memristor emulator circuits exploiting a dynamic threshold feature of MOSFET and requiring no DC bias have been presented here. The propositions herein require no external capacitors. In these two circuit propositions of floating and grounded memristor emulators, the static power consumption is zero. Theoretical justifications of the propositions have been validated by

Alignment of transcription to the speech finds applications in video subtitling, human–computer interaction by means of natural language communication, etc. In spite of many advancements, alignment of transcription to speech remains a challenging task and may become even more challenging for dysarthric speech. Dysarthria is a motor speech disorder resulting from damaged peripheral or central nervous

Local processing of machine learning algorithms like support vector machine (SVM) is preferred over the cloud for many real-time embedded applications. However, such embedded systems often have stringent energy constraints besides throughput and accuracy requirements. Hence, hardware-efficient design to compute SVM is critical to enable these applications. In this paper, a hardware-efficient SVM learning

This paper presents a fixed point design and implementation of a low-complexity high-throughput digital predistorter (DPD) on FPGA. Based on the memory polynomial model, a parallel structure is proposed for the implementation of the DPD and the effects of the fixed-point implementation on the performance are analyzed employing fidelity metrics such as modulation error ratio and adjacent channel power

A methodology for designing anti-windup compensators is investigated, for sampled-data systems with delays and actuator saturation. More precisely, criteria for the existence of an anti-windup compensator that ensure simultaneously stability and an \(H_{\infty }\) norm bound in closed-loop are developed, thanks to the use of a three-term approximation of the delays, of the scaled small gain theorem

As an alternative to existing methods, we design a transform-domain algorithm to avoid the computational cost of a two-dimensional (2-D) spectral peak search when addressing the problem of joint azimuth and elevation directions-of-arrival (DOAs) estimation via an L-shaped array. Motivated by the linear prediction property of the signal cross-covariance matrix, the 2-D DOA estimation problem is equivalently

The cascaded integrator–comb (CIC) filter is a key building block for communication and sample rate conversion systems that require efficient implementation. One such example is in satellite applications. Space applications have the problem of being highly susceptible to cosmic radiation, which in turn has the possibility of corrupting data. It is therefore necessary to devise techniques that detect

The radiation efficiency of short electric dipole and small magnetic loop is low. Therefore, the long electric dipole and large magnetic loop for direction of arrival (DOA) estimation are investigated in this study. A novel array composed of long electric dipole, large magnetic loop, or a hybrid long electric dipole and large magnetic loop is proposed. Then a corresponding algorithm based on ESPRIT

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In this paper, the behaviour of a variable-order passive circuit element which is used in Chua chaotic circuit is analysed. Firstly, the behaviour of a circuit with a variable-order memristor is presented. In the generalized Ohm’s law for a memory element, the order of a passive circuit element is defined as a kind of the element, so the circuit shows unusual behaviour. Finally, the chaotic circuit

Normalization and envelope generation of signals are essential pre-processing steps in many signal processing applications. With the emergence of high-performance computing and the need for hardware accelerators in digital signal processing, research for hardware efficient solutions has become a necessity. Interpolation and signal normalization algorithms, though have been implemented in software systems

Energy detection-based spectrum sensing techniques are ideally suited for power-constrained cognitive radio applications because of their lower computational complexity compared to feature detection techniques. However, their detection performance is dependent on multiple factors like accuracy of noise variance estimation and signal-to-noise ratio (SNR). Many variations of energy detection techniques

Non-local mean (NLM) adaptive filtering is a well-explored technique for the denoising of images and electrocardiogram signals. In NLM filtering, the signal value at a particular sample point is estimated by a weighted average of sample points over a search neighborhood. The NLM filter effectively removes the noise when there are similarities among the samples of the signal over the search neighborhood

This paper proposes a spectrum sensing algorithm from one-bit measurements in a cognitive radio sensor network. A likelihood ratio test (LRT) for the one-bit spectrum sensing problem is derived. Different from the one-bit spectrum sensing research work in the literature, the signal is assumed to be a discrete random correlated Gaussian process, where the correlation is only available within immediate

Among other uses, oversampling can be useful for systems that aim to accurately estimate the time delay between two signals. Due to the simplicity of its implementation, \(\varSigma \varDelta \) analog-to-digital converters have been largely used when oversampled signals are required. In this work, two methods for parallel evaluation of the discrete Fourier transform (DFT) of \(\varSigma \varDelta

This paper is devoted to the problem of isomorphism in graphs and proposes a method based on time response of a differential equation. First it is shown that the solution of a differential equation obtaining from a Laplacian matrix can be used as an index and the proof is presented. Then a search algorithm is proposed to find out that the two graphs are isomorphic and there is a permutation matrix

In this paper, we aim to improve traditional DNN x-vector language identification performance by employing wide residual networks (WRN) as a powerful feature extractor which we combine with a novel frequency attention network. Compared with conventional time attention, our method learns discriminative weights for different frequency bands to generate weighted means and standard deviations for utterance-level

In this paper, we propose a configurable rotation matrix for Hyperbolic COordinate Rotation DIgital Computer (CORDIC) to compute any logarithm and inverse logarithm. The rotation matrix of the conventional Hyperbolic CORDIC computes only natural logarithm and natural inverse logarithm whereas the proposed rotation matrix configures the Hyperbolic CORDIC to compute any logarithm and inverse logarithm

In this paper, we investigate the problem of joint direction-of-departure (DOD) and direction-of-arrival (DOA) estimation for bistatic multiple-input multiple-output radar with unknown spatially colored noise. By exploiting the sparse structure of the noise covariance matrix, a new de-noising scheme is designed. The signal covariance matrix is recast as a low-rank matrix with missing entries, which

A foreground calibration technique for switched-current R-2R digital-to-analog converter is proposed. To implement the method, some intermediate nodes are added to the circuit and calibration is done using these nodes to circumvent both current source and resistor mismatches at the output node. A 12-bit, 500-MHz DAC is designed in 0.18 \(\upmu \)m standard CMOS technology with the proposed technique

Underdetermined blind source separation (UBSS) is an important issue for sparse signals, and a novel two-step approach for UBSS based on the law of large numbers and minimum intersection angle rule (LM method) is presented. In the first step, an estimation of the mixed matrix is obtained by using the law of large numbers, and the number of source signals is displayed graphically. In the second step

Image deblurring is a fundamental problem in imaging field which often needs to recover the important structure of images. This paper addresses the image deblurring problem by considering an image as a combination of its cartoon (the piecewise smooth part of the image) and texture (the oscillation part of the image) components. To recover both of these parts, we propose the use of coupled analysis-based

In this paper, we propose a novel parameter-free Landweber iteration (LI) method to improve the robustness of a beamformer based on the LI algorithm and the L-curve criterion. The critical aspect of the proposed method is the automatic parameter selection procedure, which determines the iteration stop number in a scenario-dependent manner. This parameter-free method can flexibly adapt to different