JOURNAL OF IRANIAN ASSOCIATION OF ELECTRICAL AND ELECTRONICS ENGINEERS
Year:2012 | Volume:9 | Issue:1|Papers Count:7

Almost all logic systems have a main clock signal in order to provide a common timing reference for all of the components in the system. Supporting the highest bandwidth data rates among devices requires advanced clock management technology such as delay-locked loops (DLLs). The DLL circuitry allows for very precise synchronization of external and internal clocks. In this paper a low jitter and wide operation range Mixed-Mode Delay Locked Loop is presented. A multiperiodlocked technique is used to enhance the input frequency Range. Moreover, a new CP is proposed to suppress mismatch problem in single ended CPs. In this way jitter and static phase error specifications have been improved. The designed circuit has been simulated in ADS software, using TSMC 0.18 um CMOS process at 1.8V supply voltage. Simulation results show that the frequency range of the suggested DLL is from 170 to 1100 MHz. The rms jitter and power dissipation of the designed circuit at 1100 MHz are 3.3 psec and 4.554 mW, respectively.

In radar detection, the existence of the clutter edge in the reference samples considerably degrades the performance of the detector. Hence, clutter edge estimation not only improves the CFAR detectors, but also can be used for partitioning the various areas of the clutter in the clutter map. In this paper, we propose an adaptive algorithm for detecting the clutter edge between two Weibull clutter areas with different shape and scale parameters. First, we apply the UMPI detector as a data pre-processor which is optimal among the invariant detectors. Then, based on the results of the previous pre-detection, the reference data are partitioned by an adaptive algorithm and the position of the clutter edge is estimated. For this, we need to the probability density functions of the pre-detector output samples which are provided by the nearest neighbor method.

One of the basic problems in signature verification is variability and differences apparent on patterns of signature even for an individual. Signature segmentation to basic components, in addition to the access to the stable features, the hidden differences are revealed between genuine and forgery patterns. In this paper, signature patterns of two-dimensional are segmented by using dominant points. Segmentation decrease computation complexity also classification error of genuine and forgery signatures reduces. With extraction of strokes and one to one mapping their on the reference and test patterns based on algorithm of optimal subsequence bijection, parameter and functional features are defined. Applying the proposed approach to database extensive database with people in Farsi, Chinese, English and Turkish and contextual classification using linear, Parzen window and support vector machines, EER are 1.75% and 2.12% in group forger random and skilled, respectively.

In this paper, Automatic electrocardiogram (ECG) arrhythmias classification is essential to timely diagnosis of dangerous electromechanical behaviors and conditions of the heart. In this paper, a new method for ECG arrhythmias classification using wavelet transform (WT) and neural networks (NN) is proposed. Here, we have used a discrete wavelet transform (DWT) for processing ECG recordings, and extracting some time frequency features to be used for training a multi-layered perceptron (MLP) neural network. In fact, the MLP NN performs the classification task. Although many algorithms have been presented for ECG arrhythmias detection over the past years, the results reported in the past, have generally been limited to relatively small set of data patterns. Here, we have used 20 recordings of the MIT-BIH arrhythmias data base for training and testing our neural network based classifier. The simulation results show that the classification accuracy of our method is 97% over 420 patterns using 20 files including four arrhythmias.

This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.

The induction or synchronous motor can temporarily produce voltage such as a generator after disconnection from the power system. Subsequently, voltage and frequency differences between the motor terminal and the power system are gradually increased. In such conditions, the mechanical damages to motor may be occurred during motor reconnection when the synchronizing conditions are not complied. To overcome this problem, several methods have been proposed in the literature to reconnect a motor to the power system based on the bus transfer approach. In this paper, several bus transfer methods such as parallel transfer, fast transfer, delayed transfer, residual voltage transfer, and in-phase transfer are investigated based on simulation of an industrial system. Afterwards, a novel adaptive bus transfer technique is proposed to minimize the imposed thermal and mechanical stresses on the electrical motor.

This paper proposes an efficient and novel method for transmission expansion planning in regulated environment of power systems. The method is based on combination of two algorithms such as special genetic algorithm (GA) and constructive heuristic algorithm. The proposed GA has its own special characteristics that make it better than other metahuristic methods in transmission expansion planning problems. The improvement phase is the main characteristic that makes this type of GA more efficient. It means that if after mating procedure (selection, crossover and mutation), the offspring was an infeasible one, by using a suitable constructive heuristic algorithm, and the aforementioned offspring is changed to a feasible one. Also by using a relaxed linear model of TEP and importing cost perturbation, a qualified initial population is obtained and used as an initial population of GA. The simulation results obtained from the proposed method were compared to those achieved from previous literature in terms of solution quality and computational efficiency. Results reveal that the superiority of this method in both aspects of financial and CPU time.