A linear hybrid multi-user detector in synchronous direct sequence code division multiple access systems (DS/CDMA) is performed by using linear successive interference cancellation detector (SIC) and linear decorrelator detector in order to exploit the advantages offered by the two detectors. Its main objectives are to reduce the long detection delay times and to improve the performance compared to that of the conventional SIC. Finally, theoretical and simulation results are in perfect agreement demonstrating the effectiveness of the elaborated scheme.

A novel type2-fuzzy adaptive filter is presented, which uses the concepts of type2-fuzzy logic, for electrocardiogram signals denoising. Type2-fuzzy adaptive filter is an information processor where both numerical and linguistic information are used as input-output pairs and fuzzy if-then rules, respectively. The proposed approach is based on an iterative procedure to achieve acceptable information extraction in the case where the statistical characteristics of the input-output signals are unknown. The proposed filter is presented as a dual-layered feedback system. Each layer has different function, the first layer being the type2-fuzzy autoregressive filter model. The second layer being responsible for training the membership function parameters. The second layer adjusts the type2-fuzzy adaptive filter parameters by using a teaching learning-based optimization algorithm (TLBO), which will allow the reaching of the required signal reconstruction by decreasing the criterion function. The proposed filter is validated and evaluated through some experimentations using the MIT-BIH ECGs databases where various artifacts were added to the ECGs signals; these included real and artificial noise. For comparison purposes, both model and non-modelbased methods recently published are used. Furthermore, the effect of the proposed filter on the malformation of diagnostic features of the ECG was studied and compared with several benchmark schemes. The results show that the proposed method performs better denoising for all noise power levels and for a different criteria viewpoint.

We propose a new approach for modeling a High Electron Mobility Transistor (HEMT) using that of Gaussian Process Regression one (GPR), to improve the current-voltage characteristics of HEMT transistor for using in electronic and biological domain or any other domain that needs it. The study and development of a new Atlas Silvaco device are taking into account the impact of several geometric and electric parameters; we focus on the electrical performances of the double gate field plate In0.2Ga0.8As/Al0.3Ga0.7As HEMT including double heterostructure; we compare the numerical simulation using 2D Atlas Silvaco simulator with the extracted experimental results. Then we validate our model by GPR approach. The GPR approach opens promising opportunities for devices modeling without knowing too much the device physics properties. The obtained results give better performances which lead to fabricate devices with better electrical properties for promoting further investigation.

This paper presents a hybrid strategy combining compact analytical models of short channel Gate-All-Around Junctionless (GAAJ) MOSFET and metaheuristic-based approach for parameters optimization. The proposed GAAJ MOSFET design includes highly extension regions doping. The aim is to investigate the impact of this design on the RF and analog performances systematically and to show the immunity behavior against the short channel effects (SCEs) degradation. In this context, an analytical model via the meticulous solution of 2D Poisson equation, incorporating source/drain (S/D) extensions effect, has been developed and verified by comparing it with TCAD simulation results. A comparative evaluation between the proposed GAAJ MOSFET structure and the classical device in terms of RF/Analog performances is also investigated. The proposed design provides RF/Analog performances improvement. Furthermore, based on the presented analytical models, Genetic Algorithms (GA) optimization approach is used to optimize the design of S/D parameters. The optimized structure exhibits better performances, i.e., cut-off frequency and drive current are improved. Besides, it shows superior immunity behavior against the RF/Analog degradation due to the unwanted SCEs. The insights offered by the proposed paradigm will help to enlighten designer in future challenges facing the GAAJ MOSFET technology for high RF/analog applications.

Unlike traditional visual cryptography based on a threshold mechanism in which the secret image can be revealed by stacking k,(2≤k≤n) shadows or more. In our suggested (kk,nn) progressive secret sharing scheme with unexpanded pixel, we could obtain until n−1n−1 revealed secret images with progressive enhanced contrast in an increasing way from the lowest quality, in the case of stacking two shares, to a highest quality in the case of stacking all the nn shares. Our scheme not only has the advantage of the unexpanded shares, but also the use of very simple Boolean XOR and OR operations to recover the secret image perfectly. Moreover, the proposed scheme does not need any codebooks to construct shares. The experimental results indicate the privilege of our method compared with the other related work.

Electrocardiogram (ECG) signals are often contaminated with artefacts and noises which can lead to incorrect diagnosis when they are visually inspected by cardiologists. In this paper, the well-known discrete Fourier series (DFS) is re-explored and an efficient DFS-based method is proposed to reduce contribution of both baseline wander (BW) and powerline interference (PLI) noises in ECG records. In the first step, the determination of the exact number of low frequency harmonics contributing in BW is achieved. Next, the baseline drift is estimated by the sum of all associated Fourier sinusoids components. Then, the baseline shift is discarded efficiently by a subtraction of its approximated version from the original biased ECG signal. Concerning the PLI, the subtraction of the contributing harmonics calculated in the same manner reduces efficiently such type of noise. In addition of visual quality results, the proposed algorithm shows superior performance in terms of higher signal-to-noise ratio and smaller mean square error when faced to the DCT-based algorithm.

In this paper, state variables estimation and Fuzzy Sliding Mode Control (FSMC) are presented in order to estimate the state variables and altitude-attitude tracking control in presence of internal and external disturbances for unmanned quadrotor. The main idea of the proposed control strategy is the development of an Extended Kalman Filter (EKF) for the observation of the states. Fuzzy logic systems are used to adapt the unknown switching-gains to eliminate the chattering phenomenon induced by Sliding Mode Control (SMC). The stability of the system is guaranteed in the sense of Lyapunov. The effectiveness and robustness of the proposed controller-observer scheme that takes into account internal and external disturbances are demonstrated on computer simulation using Matlab environment.

A robust nonlinear controller based on an improved feedback linearization technique with state observer in presence of uncertainties and external disturbances is developed for a class of nonlinear systems. First, by combining classical feedback linearization approach with a robust control term and a fuzzy logic system, we design and study an efficient controller for such systems. Second, we propose an optimized extended Kalman filter for the observation of the states. The parameters to be optimized are the covariance matrices Q and G, which play an important role in the extended Kalman filter performances. This optimization is insured by the particle swarm optimization algorithm. The Lyapunov synthesis approach is used to prove the stability of the whole control loop. The proposed approach is simulated on a nonlinear inverted‐pendulum system. Simulation results demonstrate the robustness and effectiveness of the proposed scheme and exhibit a more superior performance than its conventional counterpart.

In this study, an optimized extended Kalman filter (EKF), and an interval type-2 fuzzy sliding mode control (IT2FSMC) in presence of uncertainties and disturbances are presented for robotic manipulators. The main contribution is the proposal of a novel application of Biogeography-Based Optimization (BBO) to optimize the EKF in order to achieve high performance estimation of states. The parameters to be optimized are the covariance matrices Q and R, which play an important role in the performances of EKF. The interval type-2 fuzzy logic system is used to avoid chattering phenomenon in the sliding mode control (SMC). Lyapunov theorem is used to prove the stability of control system. The suggested control approach is demonstrated using a computer simulation of two-link manipulator. Finally, simulations results show the robustness and effectiveness of the proposed scheme, and exhibit a more superior performance than its conventional counterpart.

The main purpose of this paper is to integrate fuzzy logic technique and backstepping synthesis to sliding mode control to develop a Fuzzy Backstepping-Sliding Mode Controller (FBSMC) to resolve the problem of altitude and attitude tracking control of unmanned quadrotor systems under large external disturbances. First, a backstepping-sliding mode control for quadrotor is introduced. Moreover, a fuzzy logic system is employed to adapt the unknown switching gains to eliminate the chattering phenomenon induced by switching control on the conventional Backstepping-Sliding Mode Controller (BSMC). The dynamical motion equations are obtained by EulerNewton formalism. The stability of the system is guaranteed in the sense of the Lyapunov stability theorem. Simulation results are carried out using Matlab/Simulink environment to illustrate the effectiveness and robustness of the proposed controller.

Baseline wander (BW) is a common low frequency artifact in electrocardiogram (ECG) signals. The prime cause from which BW arises is the patient's breathing and movement. To facilitate reliable visual interpretation of the ECG and to discern particular patterns in the ECG signal, BW needs to be removed. In this paper, a novel BW removal method is presented. The hypothesis is based on the observation that ECG signal variation covaries with its BW. As such, the P, Q, R, S, and T peaks will follow the baseline drift. On this basis, the following proposition is true: a reliable approximation of the baseline drift can be obtained from the shape derived from the interpolation of one form of the ECG signal peak (peak envelope). The simulation was performed by adding artificial BW to ECG signal recordings. The signal-to-noise ratio, mean squared error, and improvement factor criteria were used to numerically evaluate the performance of the proposed approach. The technique was compared to that of the Hilbert vibration decomposition method, an empirical-mode decomposition technique and mathematical morphology. The results of the simulation indicate that the proposed technique is most effective in situations where there is a considerable distortion in the baseline wandering.

In this investigation a novel type-2 fuzzy model for electrophysiological signals is presented. It is based on interval type-2 fuzzy systems. This method can deal with the curve fitting and computational time problems of type-2 fuzzy systems. This approach will significantly reduce the number of type-2 fuzzy rules and simultaneously preserve the fitting quality. The proposed model comprises a parallel interconnection of two type-2 sub-fuzzy models. The first is the primary model, which represents an ordinary model with a low resolution for the electrophysiological signal under consideration, the second is a fuzzy sub-model called the error model, which represents uncertainty in the primary model. Identification is achieved by innovative metaheuristic optimisation algorithms. The method's effectiveness is evaluated through testing on synthetic and real ECG signals. In addition, a detailed comparative study with several benchmark methods will be given. Intensive computer experimentations confirm that the proposed method can significantly improve convergence and resolution.

In any wireless cellular network, power control is one of the most important dynamic radio resource management (RRM) schemes which increases the capacity and performance of the system. In this paper, we present a modified scheme to Distributed Power control that optimize the transmission power of mobile’s and signal-to-interference-plus-noise ratio (SINR) error. This method, based on minimization of performance criterion, achieves the minimum SINR error and power consumption at the next time instant. The Mixed Kalman/H∞ Filter with covariance intersection has been applied in the proposed scheme to estimate and predict the channel variation and still ensure a good robustness. Finally, the mixed Kalman/H∞ filter based power control method is compared with Kalman filter and H∞ filter based power control results show that our method provides robustness against practical impairments, such as measurement uncertainties and fast channel variations.

High order modulation (HOM) presents a key challenge in increasing spectrum efficiency in 4G and upcoming 5G communication systems. In this paper, two non-linear adaptive equalizer techniques based on multilayer perceptron (MLP) and radial basis function (RBF) are designed and applied on HOM to optimize its performance despite its high sensitivity to noise and channel distortions. The artificial neural network’s (ANN) adaptive equalizer architectures and learning methods are simplified to avoid more complexity and to ensure greater speed in symbol decision making. They will be compared with the following popular adaptive filters: least mean square (LMS) and recursive least squares (RLS), in terms of bit error rate (BER) and minimum square error (MSE) with 16, 64, 128, 256, 512 and 1024 quadrature amplitude modulation (QAM). By that, this work will show the advantage that the MLP equalizer has, in most cases, over RBF and traditional linear equalizers. © 2018 National Institute of Telecommunications. All rights reserved.

Reduction of the Total Harmonic Distortion (THD) in multilevel inverters requires resolution of complex nonlinear transcendental equations; in this paper we propose a combination of one of the best existing optimized hardware structures with the recent firefly algorithm, which was used to optimize the THD, through finding the best switching angles and guaranteeing the minimization of harmonics within a user defined bandwidth. The obtained THD through the simulation of the thirteen-level symmetric inverter has been reduced down to 5% (FFT of 60 harmonics). In order to validate the simulation results, a thirteen-level symmetric inverter prototype has been made, and practically experimented and tested with different loads. Consequently, the measured THD with resistive load was 4.7% on a bandwidth of 3 kHz. The main advantage of the achieved work is the reduction of the THD.

A robust nonlinear controller based on an improved feedback linearization technique with state observer is developed for a class of nonlinear systems with uncertainties and external disturbances. First, by combining classical feedback linearization approach with a discontinuous control and a fuzzy logic system, we design and study a robust controller for uncertain nonlinear systems. Second, we propose an optimized extended Kalman filter (EKF) for the observation of the states. The parameters to be optimized are the covariance matrices Q and R, which play an important role in the EKF performances. The particle swarm optimization algorithm insures this optimization. Lyapunov synthesis approach is used to prove the stability of the whole control loop. The proposed approach is applied on a two-link robot system under Matlab environment. Simulation results have confirmed the effectiveness of the proposed approach against uncertainties and external disturbances; and exhibited a more superior performance than the non-improved control actions.

The path-planning problem is commonly formulated to handle the obstacle avoidance constraints. This problem becomes more complicated when further restrictions are added. It often requires efficient algorithms to be solved. In this paper, a new approach is proposed where the path is described by means of Non Uniform Rational B-Splines (NURBS for short) with more additional constraints. An evolutionary technique called Particle Swarm Optimization (PSO) with three options of particles velocity updating offering three alternatives namely the PSO with inertia weight (PSO-W), the constriction factor PSO (PSO-C) and the combination of the two(PSO-WC); are used to optimize the weights of the control points that serve as parameters of the algorithm describing the path. Simulation results show how the mixture of the first two options produces a powerful algorithm, specifically (PSO-WC), in producing a compromise between fast convergence and large number of potential solution. In addition, the whole approach seems to be flexible, powerful and useful for the generation of successful smooth trajectories for robot manipulator which are independent from environment conditions.

The study of propagation characteristics is a fundamental step in mobile radio engineering; which is intended to achieve maximum performance for a mobile radio system. To do this, the propagation models are essential tools for this study such as the evaluation of the signal strength received by a mobile terminal, the evaluation of coverage radii and deduce the number of cells needed to cover a given area, such as radio planning, which in turn is the step that aims to estimate the necessary equipment and configurations of the radio interface. In this work we adopt the standard K factor model and OKUMURA HATA model to demonstrate a propagation model adapted to the physical environment of the city of Annaba in Algeria using a linear regression algorithm based on the ordinary least squares method. Radio measurements were carried out on the CDMA network of operator Mobilis. The calculation of the square root of the mean square error between the actual data and the radio measurements and the prediction data derived from the model implemented allowing the validation of the results obtained. A comparative study between the value of the RMSE obtained by the new model and those obtained by the models K standard factors and the model of OKUMURA HATA allows us to conclude that the new model is better adapted to our local environment than that of OKUMURA HATA. The new model obtained can help increase the performance of mobile radio systems deployed in our territory. © 2017, School of Electrical Engineering and Informatics. All rights reserved.

Recently, researches in the interventional microrobots have taken the lion’s share in the field of biomedical devices. The aim of biomedical microrobots is to reach inaccessible areas of the human body and deliver drugs in high position. This work presents a new approach to elaborate a new physics-based model for novel self-propelled swimming microrobots. The robot is composed of an ellipsoidal head and hybrid tail that are propelled by a joint polymer metal composite actuator. Green’s function is used to solve the coupled elastic/fluid problems caused by the vibrating hybrid tail in a fluid. This method allowed producing the velocity of microrobot. For the control of the swimming microrobot in hazardous environment, the flatness-fuzzy-based control strategy is developed to eliminate the effect of nonlinear model and to generate the optimal trajectory of flat outputs. The fuzzy technique is aimed to adjust the law control gains in real time for improving the precision of the proposed microrobot in tracking the desired trajectory in fluid. The multi-objectives genetic algorithm is employed to optimize both the reference trajectory and the design parameters in order to enhance the time response and to minimize the dynamic tracking error of the trajectory. To achieve this, a numerical model based on accurate solutions of Navier–Stokes equations is developed. The results of the simulation show that the proposed design with ellipsoidal head gives better performance in comparison with that achieved by the conventional structure.