Iranian Journal of Electrical and Electronic Engineering

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A robust skin detector is the primary need of many fields of computer vision, including face detection, gesture recognition, and pornography filtering. Less than 10 years ago, the first paper on automatic pornography filtering was published. Since then, different researchers claim different color spaces to be the best choice for skin detection in pornography filtering. Unfortunately, no comprehensive work is performed on evaluating different color spaces and their performance for detecting naked persons. As such, researchers usualy refer to the results of skin detection based on the work doen for face detection, which underlies different imaging conditions. In this paper, we examine 21 color spaces in all their possible representations for pixel-based skin detection in pornographic images. Consequently, this paper holds a large investigation in the field of skin detection, and a specific run on the pornographic images.

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In this paper a new approach for design of class-AB current-mode square-root domain filters based on the electronically simulated translinear loop principle is presented. FG-MOS transistors that operate in strong inverted saturation region are employed for implementation of translinear loop circuit. The filter achieves immunity to body effect, low circuit complexity, large input dynamic range, and also works in low voltage compared to those reported before. With supply voltage 1.2V a dynamic range of 46dB at 1% THD is achieved. Simulation results by HSPICE confirm the validity of the proposed design technique and show high performance of the filter.

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This paper presents a parametric low differential order model, suitable for mathematically analysis for Induction Machines with faulty stator. An adaptive Kalman filter is proposed for recursively estimating the states and parameters of continuous–time model with discrete measurements for fault detection ends. Typical motor faults as interturn short circuit and increased winding resistance are taken into account. The models are validated against winding function induction motor modeling which is well known in machine modeling field. The validation shows very good agreement between proposed method simulations and winding function method, for short-turn stator fault detection.

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In this paper, the nonlinear lattice-Hammerstein filter and its properties are derived. It is shown that the error signals are orthogonal to the input signal and also backward errors of different stages are orthogonal to each other. Numerical results confirm all the theoretical properties of the lattice-Hammerstein structure.

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In this paper we present a general formalism for the establishment of the family of selective partial update affine projection algorithms (SPU-APA). The SPU-APA, the SPU regularized APA (SPU-R-APA), the SPU partial rank algorithm (SPU-PRA), the SPU binormalized data reusing least mean squares (SPU-BNDR-LMS), and the SPU normalized LMS with orthogonal correction factors (SPU-NLMS-OCF) algorithms are established by this general formalism. In these algorithms, the filter coefficients are partially updated rather than the entire filter coefficients at every iteration which is computationally efficient. Following this, the transient and steady-state performance analysis of this family of adaptive filter algorithms are studied. This analysis is based on energy conservation arguments and does not need to assume a Gaussian or white distribution for the regressors. We demonstrate the performance of the presented algorithms through simulations in system identification and acoustic echo cancellation scenarios. The good agreement between theoretically predicted and actually observed performances is also demonstrated

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This paper presents design and implementation of three new Infrared Counter-Countermeasure (IRCCM) efficient methods using Neural Network (NN), Fuzzy System (FS), and Kalman Filter (KF). The proposed algorithms estimate tracking error or correction signal when jamming occurs. An experimental test setup is designed and implemented for performance evaluation of the proposed methods. The methods validity is verified with experiments on IR seeker reticle based on a Digital Signal Processing (DSP) processor. The practical results emphasize that the proposed algorithms are highly effective and can reduce the jamming effects. The experimental results obtained strongly support the potential of the method using FS to eliminate the IRCM effect 83%.

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In this paper, chiral E-shaped resonators are used in a waveguide. Direction of EM wave and position of resonators for effective excitation is studied and various resonances of E-shaped resonators are determined. As a consequence an analytical equivalent circuit model is proposed. Finally, an array of these resonators is used to realize a wide reject band. The resulted band stop filter performance is simulated and a rejection level of almost 40 dB is achieved to confirm the effectiveness of the idea. This stopband filter is used in cascade with a bandpass filter to suppress its spurious response.

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In order to detect targets upon sea surface or near it, marine radars should be capable of distinguishing signals of target reflections from the sea clutter. Our proposed method in this paper relates to detection of dissimilar marine targets in an inhomogeneous environment with clutter and non-stationary noises, and is based on adaptive thresholding determination methods. The variance and the mean values of the noise level have been estimated in this paper, based on non-stationary, statistical methods and thresholding has been carried out using the suggested two-pole recursive filter. Making the rate of false alarm constant, the concerned threshold resolves the hypothesis of existence or absence of the target signal. Performance of the mentioned algorithm has been compared with the well-known conventional method as CA-CFAR in terms of decreasing the losses and increasing calculation speed. The algorithm provided for detection of signal has been implemented as a part of signal-processing algorithms of some practical marine radar. The results obtained from the algorithm performance in a real environment indicate appropriate workability of this method in heterogeneous environment and non-stationary interference.

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Two-dimensional (TD) adaptive filtering is a technique that can be applied to many image, and signal processing applications. This paper extends the one-dimensional adaptive filter algorithms to TD structures and the novel TD adaptive filters are established. Based on this extension, the TD variable step-size normalized least mean squares (TD-VSS-NLMS), the TD-VSS affine projection algorithms (TD-VSS-APA), the TD set-membership NLMS (TD-SM-NLMS), the TD-SM-APA, the TD selective partial update NLMS (TD-SPU-NLMS), and the TD-SPU-APA are presented. In TD-VSS adaptive filters, the step-size changes during the adaptation which leads to improve the performance of the algorithms. In TD-SM adaptive filter algorithms, the filter coefficients are not updated at each iteration. Therefore, the computational complexity is reduced. In TD-SPU adaptive algorithms, the filter coefficients are partially updated which reduce the computational complexity. We demonstrate the good performance of the proposed algorithms thorough several simulation results in TD adaptive noise cancellation (TD-ANC) for image restoration. The results are compared with the classical TD adaptive filters such as TD-LMS, TD-NLMS, and TD-APA

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In recent years chaotic secure communication and chaos synchronization have received ever increasing attention. Unfortunately, despite the advantages of chaotic systems, Such as, noise-like correlation, easy hardware implementation, multitude of chaotic modes, flexible control of their dynamics, chaotic self-synchronization phenomena and potential communication confidence due to the very dynamic properties of chaotic nonlinear systems, the performance of most of such designs is not studied and so is not still suitable for wireless channels. To overcome this problem, in this paper a novel wide-band chaos-based communication scheme in multipath fading channels is presented, where the chaotic synchronization is implemented by particle filter observer. To illustrate the effectiveness of the proposed scheme, numerical simulations based on particle filter are presented in different channel conditions and the results are compared with two other EKF and UKF based communication scheme. Simulation results show the Remarkable BER performance of the proposed particle filter-based system in both AWGN and multipath fading channels condition, causes this idea act as a good candidate for asynchronous wide band communication.

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This paper presents the design and a new low-cost process for fabrication of a second-order micromechanical filter using UV-LIGA technology. The micromechanical filter consists of two identical bulk-mode ring resonators, mechanically coupled by a flexural-mode beam. A new lumped modeling approach is presented for the bulk-mode ring resonators and filter. The validity of the analytical derivation is investigated using the finite element method by ANSYS software. The new low-cost fabrication process is used to achieve a high aspect ratio of 16 with 3 μm gap spacing. The rigid graphite serves as a low-cost primary substrate and plating base of nickel as structural material. The fabrication process needs only three UV-lithography steps with Mylar masks to fabricate the main structure and pattern the printed circuit board as a secondary substrate. The frequency response of the fabricated filter is characterized as a function of the DC-bias voltage using a fully differential drive and sense interface circuit. The experimental results demonstrates micromechanical filter with center frequency in the vicinity of 10.31 MHz and percent bandwidth less than 0.3% using a DC-bias voltage of 60 V. The detailed fabrication process can be applied as an appropriate low-cost alternative to X-ray LIGA and silicon-based micromechanical filters.

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This paper presents a new variable step-size normalized subband adaptive filter (VSS-NSAF) algorithm. The proposed algorithm uses the prior knowledge of the system impulse response statistics and the optimal step-size vector is obtained by minimizing the mean-square deviation(MSD). In comparison with NSAF, the VSS-NSAF algorithm has faster convergence speed and lower MSD. To reduce the computational complexity of VSSNSAF, the VSS selective partial update NSAF (VSS-SPU-NSAF) is proposed where the filter coefficients are partially updated in each subband at every iteration. We demonstrated the good performance of the proposed algorithms in convergence speed and steady-state MSD for a system identification set-up.

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A two stage sub-µW Inverter-based switched-capacitor amplifier-filter is presented which is capable of amplifying both spikes and local field potentials (LFP) signals. Here we employ a switched capacitor technique for frequency tuning and reducing of 1/f noise of two stages. The reduction of power consumption is very necessary for neural recording devices however, in switched capacitor (SC) circuits OTA is a major building block that consumes most of the power. Therefore an OTA-less technique utilizing a class-C inverter is employed that significantly reduces the power consumption. A detailed analysis of noise performance for the inverter-based SC circuits is presented. A mathematical model useful for analysis of such SC integrators is derived and a good comparison is obtained between simulation and analytical technique. With a supply voltage of 0.7V and using 0.18 µm CMOS technology, this design can achieves a power consumption of about 538 nW. The designed amplifier-filter has the gains 18.6 dB and 28.2 dB for low pass only and cascaded filter, respectively. By applying different sampling frequencies, the filter attains a reconfigurable bandwidth.

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Gaussian Mixture Models (GMMs) of power spectral densities of speech and noise are used with explicit Bayesian estimations in Wiener filtering of noisy speech. No assumption is made on the nature or stationarity of the noise. No voice activity detection (VAD) or any other means is employed to estimate the input SNR. The GMM mean vectors are used to form sets of over-determined system of equations whose solutions lead to the first estimates of speech and noise power spectra. The noise source is also identified and the input SNR estimated in this first step. These first estimates are then refined using approximate but explicit MMSE and MAP estimation formulations. The refined estimates are then used in a Wiener filter to reduce noise and enhance the noisy speech. The proposed schemes show good results. Nevertheless, it is shown that the MAP explicit solution, introduced here for the first time, reduces the computation time to less than one third with a slight higher improvement in SNR and PESQ score and also less distortion in comparison to the MMSE solution.

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This paper presents new adaptive filtering techniques used in speech enhancement system. Adaptive filtering schemes are subjected to different trade-offs regarding their steady-state misadjustment, speed of convergence, and tracking performance. Fractional Least-Mean-Square (FLMS) is a new adaptive algorithm which has better performance than the conventional LMS algorithm. Normalization of LMS leads to better performance of adaptive filter. Furthermore, convex combination of two adaptive filters improves its performance. In this paper, new convex combinational adaptive filtering methods in the framework of speech enhancement system are proposed. The proposed methods utilize the idea of normalization and fractional derivative, both in the design of different convex mixing strategies and their related component filters. To assess our proposed methods, simulation results of different LMS-based algorithms based on their convergence behavior (i.e., MSE plots) and different objective and subjective criteria are compared. The objective and subjective evaluations include examining the results of SNR improvement, PESQ test, and listening tests for dual-channel speech enhancement. The powerful aspects of proposed methods are their low complexity, as expected with all LMS-based methods, along with a high convergence rate.

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In this paper, a novel technique for the design of two-channel Quadrature Mirror Filter (QMF) banks with linear phase in frequency domain is presented. To satisfy the exact reconstruction condition of the filter bank, low-pass prototype filter response in pass-band, transition band and stop band is optimized using unconstrained indirect update optimization method. The objective function is formulated as a weighted sum of pass-band error and stop-band residual energy of low-pass prototype filter, and the square error of the distortion transfer function of the QMF bank at the quadrature frequency. The performance of the proposed algorithm is evaluated in terms of Peak Reconstruction Error (PRE), mean square error in pass-band and stop-band regions and stop-band edge attenuation. Design examples are included to illustrate the performance of the proposed algorithm and the quality of the filter banks that can be designed.

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The matrix converter instability can cause a substantial distortion in the input currents and voltages which leads to the malfunction of the converter. This paper deals with the effects of input filter type, grid inductance, voltage fed to the modulation algorithm and the synchronous rotating digital filter time constant on the stability and performance of the matrix converter. The studies are carried out using eigenvalues of the linearized system and simulations. Two most common schemes for the input filter (LC and RLC) are analyzed. It is shown that by a proper choice of voltage input to the modulation algorithm, structure of the input filter and its parameters, the need for the digital filter for ensuring the stability can be resolved. Moreover, a detailed model of the system considering the switching effects is simulated and the results are used to validate the analytical outcomes. The agreement between simulation and analytical results implies that the system performance is not deteriorated by neglecting the nonlinear switching behavior of the converter. Hence, the eigenvalue analysis of the linearized system can be a proper indicator of the system stability.

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This paper presents a simple and easy implementable Least Mean Square (LMS) type approach for frequency estimation of three phase power system in an unbalanced condition. The proposed LMS type algorithm is based on a second order recursion for the complex voltage derived from Clarke's transformation which is proved in the paper. The proposed algorithm is real adaptive filter with real parameter (not complex) which can be efficiently implemented by DSP. In unbalanced situations, simulation experiments show the advantages and drawbacks of the proposed algorithm in comparison to Complex LMS (CLMS) and Augmented Complex LMS (ACLMS) methods

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The Global Positioning System (GPS) signals are very weak signal over wireless channels, so they are vulnerable to in-band interferences. Therefore, even a low-power interference can easily spoof GPS receivers. Among the variety of GPS signal interference, spoofing is considered as the most dangerous intentional interference. The spoofing effects can mitigate with an appropriate strategy in the receiver. In this paper, we use methods of adaptive filter based on Least Mean Squares (LMS) and Normalized Least Mean Squares (NLMS) algorithms in-order to defense against spoofing. The proposed techniques are applied in the acquisition stage of the receiver. The proposed methods have been implemented on real dataset. The results explain that the suggested algorithms significantly decrease spoofing. Also, they improve Position Dilution of Precision (PDOP) parameter. Based on the results, NLMS algorithm has better performance than LMS algorithm.

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Hysteresis current control method is vastly used in PWM inverters because of simplicity in performance, fast control response and good ability in limiting peak current. However, switching frequency in hysteresis current control method with fixed bandwidth has large variation during a cycle and therefore causes non-optimal current ripple generation in output current. One of basic problems in implementing hysteresis current control is its variable switching frequency that causes sound noise and increase in inverter losses and also high frequency current components injection to the source current. In this paper, in addition to the calculation of variable hysteresis bandwidth equation that fixes frequency switching, also other problems can be solved by removing the derivative part. Here, a shunt active filter has been used for removing the current harmonic components generated by non-linear loads. Proposed method is simple to perform and reliable, and also has been simulated in MATHLAB software environment