Iranian Journal of Electrical and Electronic Engineering

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The aim of this study is to introduce a new methodology for isolation of ectopic rhythms of ambulatory electrocardiogram (ECG) holter data via appropriate statistical analyses imposing reasonable computational burden. First, the events of the ECG signal are detected and delineated using a robust wavelet-based algorithm. Then, using Binary Neyman-Pearson Radius test, an appropriate classifier is designed to categorize ventricular complexes into "Normal + Premature Atrial Contraction (PAC)" and "Premature Ventricular Contraction (PVC)" beats. Afterwards, an innovative measure is defined based on wavelet transform of the delineated P-wave namely as P-Wave Strength Factor (PSF) used for the evaluation of the P-wave power. Finally, ventricular contractions pursuing weak P-waves are categorized as PAC complexes however, those ensuing strong P-waves are specified as normal complexes. The discriminant quality of the PSF-based feature space was evaluated by a modified learning vector quantization (MLVQ) classifier trained with the original QRS complexes and corresponding Discrete Wavelet Transform (DWT) dyadic scale. Also, performance of the proposed Neyman-Pearson Classifier (NPC) is compared with the MLVQ and Support Vector Machine (SVM) classifiers using a common feature space. The processing speed of the proposed algorithm is more than 176,000 samples/sec showing desirable heart arrhythmia classification performance. The performance of the proposed two-lead NPC algorithm is compared with MLVQ and SVM classifiers and the obtained results indicate the validity of the proposed method. To justify the newly defined feature space (σi1, σi2, PSFi), a NPC with the proposed feature space and a MLVQ classification algorithm trained with the original complex and its corresponding DWT as well as RR interval are considered and their performances were compared with each other. An accuracy difference about 0.15% indicates acceptable discriminant quality of the properly selected feature elements. The proposed algorithm was applied to holter data of the DAY general hospital (more than 1,500,000 beats) and the average values of Se = 99.73% and P+ = 99.58% were achieved for sensitivity and positive predictivity, respectively.

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Wide band code division multiple access (WCDMA) signals, transmitted by the base station high power amplifiers (HPAs), show high peak to average power ratios (PAPR), which results in nonlinear distortions. In this paper, using computer simulations effect of using a predistorted HPA on the symbol error rate (SER) of multi-user detectors in terms of output back-off (OBO) in the transmit power is analyzed. As well, using polynomials for modeling predistorters to remove nonlinear distortions of traveling wave tube amplifiers (TWTAs) and of solid state power amplifiers (SSPAs), effect of different degrees of polynomials on the SER is investigated. Simulation results show that a polynomial of degree 4 is a sufficient degree polynomial, which fits to the AM/AM characteristic of the predistorter for TWTAs. As well, for solid state power amplifiers (SSPAs) with different p values, different approximations are considered and sufficient degree polynomials are found.

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In this paper, we propose smart step closed-loop power control (SSPC) algorithm and base station assignment based on minimizing the transmitter power (BSAMTP) technique in a direct sequence-code division multiple access (DS-CDMA) receiver in the presence of frequency-selective Rayleigh fading. This receiver consists of three stages. In the first stage, with conjugate gradient (CG) adaptive beamforming algorithm, the desired users’ signal in an arbitrary path is passed and the inter-path interference is canceled in other paths in each RAKE finger. Also in this stage, the multiple access interference (MAI) from other users is reduced. Thus, the matched filter (MF) can be used for the MAI reduction in each RAKE finger in the second stage. Also in the third stage, the output signals from the matched filters are combined according to the conventional maximal ratio combining (MRC) principle and then are fed into the decision circuit of the desired user. The simulation results indicate that the SSPC algorithm and the BSA-MTP technique can significantly improve the network bit error rate (BER) in comparison with other algorithms. Also, we observe that significant savings in total transmit power (TTP) are possible with our proposed methods.

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In this paper a brushless permanent magnet motor is designed considering minimum thrust ripple and maximum thrust density (the ratio of the thrust to permanent magnet volumes). Particle Swarm Optimization (PSO) is used as optimization method. Finite element analysis (FEA) is carried out base on the optimized and conventional geometric dimensions of the motor. The results of the FEA deal to the significant improvement of the all objective functions.

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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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Prediction of peak loads in Iran up to year 2011 is discussed using the Radial Basis Function Networks (RBFNs). In this study, total system load forecast reflecting the current and future trends is carried out for global grid of Iran. Predictions were done for target years 2007 to 2011 respectively. Unlike short-term load forecasting, long-term load forecasting is mainly affected by economy factors rather than weather conditions. This study focuses on economical data that seem to have influence on long-term electric load demand. The data used are: actual yearly, incremental growth rate from previous year, and blend (actual and incremental growth rate from previous years). As the results, the maximum demands for 2007 through 2011 are predicted and is shown to be elevated from 37138 MW to 45749 MW for Iran Global Grid. The annual average rate of load growth seen per five years until 2011 is about 5.35%

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A novel ZVZCS isolated dual series-resonant active-clamp dc–dc converter is proposed to obtain high efficiency. The proposed converter employs an active-clamp technique, while a series-resonant scheme controls the output voltage with the complementary pulse width modulation controller. The active-clamp circuit serves to recycle the energy stored in the leakage inductance or the magnetizing inductance and provides zero-voltage and zero-current turn-on and turn off switching. The voltage stresses of the main switch are clamped. The voltage transient spikes across the dual series active clamp circuit and the current stress of the current-fed side switches are limited by auxiliary active clamping circuits on both sides, and ZVZCS is achieved. The operating principles and design considerations are discussed and verified by simulations using PSIM software. Also, the EMI reduction techniques from EMC point of view in the circuits related to converters has been pointed out.

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