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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

This paper investigates the finite-time robust passive control of nonlinear discrete time-delay systems via static output feedback. The considered discrete time-delay system has uncertain terms which are due to parametric uncertainties and exogenous disturbances. The disturbances are unknown time-varying signals with known upper bounds. In order to design the suitable control law, some sufficient conditions

For the problem of motion state estimation of mobile target tracked by sensor nodes, the information-weighted Kalman consensus filter (IKCF) is introduced for sensor networks with switching communication topologies. In order to improve the dynamic performance of the IKCF, the low-pass consensus filtering algorithm is used to estimate the motion acceleration of the target. Moreover, an improved low-pass

The design of filter banks with multiple centers of symmetry is very difficult. In this paper, a space decomposition of an orthogonal projection matrix is studied. This decomposition plays a key role in a new complete factorization theory. In addition, the concept of a minimal starting block matrix is proposed and is used to establish a new factorization of a 2m-band paraunitary polyphase matrix with

In this paper, the authors propose a novel model order reduction method integrating evolutionary and conventional approaches for higher-order linear time-invariant single-input–single-output (SISO) and multi-input–multi-output (MIMO) dynamic systems. The proposed method makes use of a differential evolution algorithm with enhanced mutation operation for the determination of reduced order model (ROM)

This paper extends the concept of Karnaugh map from a logical function to a logical system, thereby allowing both the state transition graph and state transition matrix of a logical system, as well as a digital circuit, to be constructed directly. It is found that the Karnaugh map of a logical system is actually a two-dimensional state transition table or, equivalently, a table-like state transition

In the past years, several QRS complex (Q, R and S wave) detecting algorithms have been implemented in software, but they are not applicable for real-time operation due to their mathematical complexity. Hence, this paper focuses on developing an algorithm which enables detection of QRS complex in real time. Here, Integer Haar Wavelet Transform is employed which is used for the purpose of filtering

To reduce the computational complexity and enhance the convergence rate, this article presents set-membership least mean square adaptive algorithms based on an error-estimation time-varying bound method. The bound is constituted by the estimation error for the previous iteration and a time-varying error adjustment factor. The set-membership (SM) method utilizes the estimation error for the current

The passivity, low power consumption, memory characteristics and nanometer size of memristors make them the best choice to simulate synapses in artificial neural networks. In this paper, based on the proposed associative memory rules, we design a memristor neural network with plasticity synapses, which can perform analog operations similar to its biological behavior. For the memristor neural network

Most models of PN junction diode are mathematical models rather than circuit models, and there is a necessary trade-off between model versatility and accuracy. The small-signal fractional-order circuit model of PN junction long-base diode based upon the device’s physical operating principles and fractional-order vector fitting is obtained. This model consists of fractional elements and traditional

The paper presents an auditory distance perception model that is based on the extraction of statistical properties from monaural and binaural features in a reverberant room environment. The developed framework has considered both mono and stereo speech signals originated from different distances at various reverberation time periods. Hence, two models, namely single-channel monaural statistics and

We propose a novel modeling method for circuits containing arbitrary nonlinear 3-terminal devices, which operates in the wave digital (WD) domain. This approach leads to the definition of a general and flexible WD model for 3-terminal devices, whose number of ports varies from 1 to 6. The generality of the method is confirmed by the fact that the WD models of 3-terminal devices already discussed in

In this paper, the finite-time state estimation problem is studied for nonlinear systems. For reducing the waste of resources which is caused by data transmission, an event-triggered mechanism is adopted to release the measurement output of nonlinear systems to the estimator when the triggered function is satisfied. The error system is obtained by estimating the state of nonlinear systems. We obtain

In this paper, a new monaural singing voice separation algorithm is presented. This field of signal processing provides important information in many areas dealing with voice recognition, data retrieval, and singer identification. The proposed approach includes a sparse and low-rank decomposition model using spectrogram of the singing voice signals. The vocal and non-vocal parts of a singing voice

The Wiener nonlinear system is composed of a linear dynamic subsystem in series with a static nonlinear subsystem. This type of system is widely found in the petroleum, chemistry, thermal and other process industries. It is of great significance to obtain the parameter estimates of the Wiener systems. This paper studies the identification problem of the Wiener time delay nonlinear system. Based on

In this paper, an adaptive tracking control problem is addressed for a class of uncertain nonlinear systems with input delay and perturbations. To design the desired adaptive controller, Pade approximation approach is introduced to handle the problem from the input delay. In addition, to avoid the problem from “explosion of complexity” existing in the conventional backstepping design, a dynamic surface

Noise reduction is an essential part of the signal processing for error-free analysis and critical measurements of the signal. Various robust mixed norm (RMN)-based adaptive algorithms have been reported to remove Gaussian and impulsive noise together. In this paper, a modified robust mixed norm (MRMN) with step-size scaler-based adaptive filter has been proposed to suppress the impulsive and Gaussian

In this paper, a new method is proposed for estimating the frequency of a complex sinusoidal signal in multiplicative and additive noise. The proposed method is based on the linear prediction property of the signals’ autocorrelation function. This frequency estimation method is a closed-form algorithm which can directly estimate the frequency without peak searching. The performance of the proposed

Neurons are regarded as basic, structural and functional units of the central nervous system. They play an active role in the collection, storing and transferring of the information during signal processing in the brain. In this paper, we investigate the dynamics of a model of a 4D autonomous Hopfield neural network (HNN). Our analyses highlight complex phenomena such as chaotic oscillations, periodic

The availability of multi-sensor and multi-resolution images obtained through earth observation satellites has given rise to a greater need for fusion technology. Fusion can provide comprehensive information about a particular scene or area by bringing the information of two or more images into a single plane. The technique has been in use for the past three decades, and several methodologies have

This paper focuses on the problem of the DOA estimation of coherent signals for the acoustic vector-sensor arrays (AVSAs) in the presence of the isotropic ambient noise. We propose a high-resolution DOA estimation method based on the acoustic intensity principle and the sparse representation technique. First, two cross-covariance matrices are constructed by employing the acoustic pressure and particle

Reversible data hiding in encrypted images (RDHEI) is a widely used technique for privacy protection, which has been developed in many applications that require high confidentiality, authentication and integrity. Proposed RDHEI methods do not allow high embedding rate while ensuring losslessly recover the original image. Moreover, embedding computational complexity and embedding rate are not satisfactory

In this paper, the problem of robust fault detection is investigated for nonlinear uncertain Markovian jump systems subject to time-varying delays, Lipschitz nonlinearities and parameter uncertainties under the event-triggered protocol. The event-triggered mechanism is introduced to adjust the transmission frequency of the data sent to the remote module. An event-based fault detection method is presented

The problem of the observer-based event-triggered control for a more general class of time-delay systems with actuators failure is investigated. Firstly, due to the system state cannot be measured in practice, a state feedback observer is used to reconstruct the state of the system. Then, based on the switching method, a solution for controller is derived such that the resulting closed-loop system

This paper considers the dynamic output feedback (DOF) control problems for a class of uncertain discrete-time singularly perturbed systems by using reduced-order subsystems (ROSs). A sufficient condition in terms of a linear matrix inequality (LMI) is provided to guarantee the existence of the DOF controller of the ROSs. The corresponding controller gain matrices can be solved by the proposed LMIs

This study presents two auxiliary variable-based identification algorithms for uncertain-input models. The auxiliary variable-based least squares algorithm can obtain unbiased parameter estimates by introducing suitable auxiliary variable vectors. Furthermore, an auxiliary variable-based recursive least squares algorithm is proposed to reduce the computational efforts. To validate the framework and

Affine projection algorithms have shown robustness against highly correlated input signals. To make the affine projection algorithm applicable for parameter estimation in wireless sensor networks, this work proposed a novel distributed affine projection algorithm by using the adapt-then-combine (ATC) scheme of the diffusion strategy. However, poorly performing nodes can potentially degrade to estimation

This paper presents a novel symmetrical phase frequency detector (PFD) sensitive to the falling edge of input clocks. Notably, the new PFD has an open-loop structure and no reset path, since UP and DN (outputs of the PFD) are never allowed to reach logic high simultaneously. Hence, the blind zone is completely eliminated in this case. Dead zone has been reduced to a great extent about 68 fs. Meanwhile

This article presents the low-power ternary arithmetic logic unit (ALU) design in carbon nanotube field-effect transistor (CNFET) technology. CNFET unique characteristic of geometry-dependent threshold voltage is employed in the multi-valued logic design. The ternary logic benefit of reduced circuit overhead is exploited by embedding multiple modules within a block. The existence of symmetric literals

Viterbi algorithm (VA) on time frequency (TF) distribution is a highly performed instantaneous frequency (IF) estimator. However, inaccurate IFs may be tracked due to switch problem in VA when signal components are overlapped on the TF plane. In order to address the problem, this paper first assumes the IF linearity in the overlapped TF regions should not change much, then, a new penalty function describing

The total variability model (TVM)/probabilistic linear discriminant analysis (PLDA) framework is one of the most popular methods for speaker verification. In this framework, the i-vector representations are first extracted from utterances via an estimated TVM and then employed to estimate the PLDA parameters for classification. The TVM and PLDA are estimated serially, so the information loss in the

This paper introduces a fractional-order eardrum Type-II model, which is derived using fractional calculus to reduce the number of elements compared to its integer-order counterpart. The proposed fractional-order model parameters are extracted and compared using five meta-heuristic optimization techniques. The CMOS implementation of the model is performed using the Design Kit of the Austria Mikro Systeme

We consider the robust principal component analysis (RPCA) problem where the observed data are decomposed to a low-rank component and a sparse component. Conventionally, the matrix rank in RPCA is often approximated using a nuclear norm. Recently, RPCA has been formulated using the nonconvex \(\ell _{\gamma }\)-norm, which provides a closer approximation to the matrix rank than the traditional nuclear

In a biopotential monitoring system, the sensors, the front end circuit, microprocessor, digital signal processor and transmitter are important blocks. The front end circuit is capable of amplifying and conditioning the biosignal. The power requirement of a biopotential monitoring system depends on the individual blocks present in the system. Direct reduction of the power is not possible in the conventional

The problem of automatic parasitic chirp components detection and suppression in a digital signal is considered. The detection is based on the calculation of the discrete Wigner distribution accompanied by the Hough transform. The filtration is achieved by a series of discrete fractional Fourier transforms converting the signal to special coordinates, where the entire energy of the parasitic signals

Power dissipation has become a major concern in nanoscale integrated circuits. The power gating and dual-supply design methods are among the most effective approaches for reducing the static and dynamic power consumptions. However, these methods require efficient data retention and voltage level conversion. In this paper, a nonvolatile level converter flip-flop (NVLCFF) is proposed to be used in ultra-low-power

This paper presents a new piecewise two-dimensional (2D) digital predistortion (DPD) method for dual-band power amplifiers (PAs). A self-organizing map network is used to divide dual-band signals into different regions. Then, a principal component analysis algorithm is used to reduce the number of predistortion coefficients in each region. The proposed method is stable in finding the optimum region

Independent component analysis (ICA), as an important data processing technique, is widely employed in many areas. The objective of the ICA is to recover independent components from observed signals. Several algorithms, such as equivariant adaptive separation via independence algorithm, least-mean-square (LMS)-type algorithms and recursive least-squares (RLS)-type learning rules, are proposed to solve

The COordinate Rotation DIgital Computer or CORDIC is an iterative algorithm for computing vector rotation. It uses only shift-and-add operations that make it a popular choice for computing operations such as vector rotation, matrix, trigonometric, hyperbolic, logarithmic and exponential computations in embedded platforms. This paper gives a control perspective to the algorithm by describing it as

The RRAM (resistive random-access memory) is one of the most competitive candidates of the emerging non-volatile memory devices. In recent years, the RRAM has been used as memory device and also to build logic circuit. However, the design method of the RRAM-based logic circuit is still an open issue. This paper proposes a design method of logic circuit based on the four-step RRAM logic gates. The design

This paper studies the problem of reduced-order extended dissipative filters design for continuous-time singular Markovian jump systems with discrete and distributed delays. By proposing a new integral inequality, a sufficient condition based on linear matrix inequalities (LMIs) is presented to ensure the existence of the extended dissipative filters. Compared with the previous ones, the proposed method

This paper presents a simple but accurate normalized nonlinear large-signal semiempirical MOS transistor model to be used in monolithic RF Class A-to-C PAs. MOS transistor characteristics, saved in lookup tables, are extracted for different PVT corners, allowing the study of the PA performance spread. Model accuracy is ratified by the excellent matching obtained when comparing data algebraically calculated

This paper presents a 922 MHz power-efficient configurable frequency-shift keying–on–off keying (FSK–OOK) phase-locked loop (PLL)-based transmitter. The proposed transmitter works as a multimode structure with configurable data rate and output power. In OOK modulation, by duty cycle adjustment of input data and producing return-to-zero data (RZ-data) by a simple circuit, the data rate can be scaled

Denoising an image, while retaining the important features of the image, has been a fundamental problem in image processing. Dual-tree complex wavelet transform is a recently created transform that offers both near shift invariance and improved directional selectivity properties. This transform has been used in many techniques, including denoising. However, these techniques have used the real and imaginary

We propose a robust attitude estimation method for multisensor systems with heavy-tailed noise. The attitude model is represented by a quaternion, and the propagation process in the filter is based on a gyro-based model. To avoid the constraint of quaternion, the quaternion is converted to modified Rodrigues parameters during the prediction and update process. Instead of the minimum mean square error

Stick–slip driving is widely applied because it provides a nearly infinite range of motion with sub-micron resolution, but its movement velocity is impacted by the dynamic response of high-voltage amplifiers. Therefore, this paper presents a high-voltage amplifier with a high dynamic response specific to stick–slip driving. Considering the capacitive load characteristic of stick–slip driving, an analog