Iranian Journal of Electrical and Electronic Engineering

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In this paper we first show that standard BP algorithm cannot yeild to a uniform information distribution over the neural network architecture. A measure of sensitivity is defined to evaluate fault tolerance of neural network and then we show that the sensitivity of a link is closely related to the amount of information passes through it. Based on this assumption, we prove that the distribution of output error caused by s-a-0 (stuck at 0) faults in a MLP network has a Gaussian distribution function. UDBP (Uniformly Distributed Back Propagation) algorithm is then introduced to minimize mean and variance of the output error. Simulation results show that UDBP has the least sensitivity and the highest fault tolerance among other algorithms such as WRTA, N-FTBP and ADP. Then a MLP neural network trained with UDBP, contributes in an Algorithm Based Fault Tolerant (ABFT) scheme to protect a nonlinear data process block. The neural network is trained to produce an all zero syndrome sequence in the absence of any faults. A systematic real convolution code guarantees that faults representing errors in the processed data will result in notable nonzero values in syndrome sequence. A majority logic decoder can easily detect and correct single faults by observing the syndrome sequence. Simulation results demonstrating the error detection and correction behavior against random s-a-0 faults are presented too.

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In an environment such as underwater channel where placing test equipments are difficult to handle, it is much practical to have hardware simulators to examine suitably designed transceivers (transmitter/receiver). The simulators of this kind will then allow researchers to observe their intentions and carry out repetitive tests to find suitable digital coding/decoding algorithms. In this paper, a simplified shallow water digital data transmission system is first introduced. The transmission channel considered here is a stochastic DSP hardware model in which signal degradations leads to a severe distortion in phase and amplitude (fades) across the bandwidth of the received signal. A computer base-band channel model with frequency non-selective feature is derived by the authors [10-11]. This system was based on fullraised cosine channel modelling and proved to be the most suitable for vertical and shortrange underwater communication csdfher), with a reflected path (specula component, when the acoustic hydrophone receives reflected signals from surface and bottom of the sea) and a random path (diffused component, when the acoustic hydrophone receives scattered signals from the volume of the sea). The model assumed perfect transmitter-receiver synchronization but utilized realistic channel time delays, and demonstrated the timevarying characteristics of an underwater acoustic channel observed in practice. In this paper, they are used to provide a full system simulation in order to design an adaptive receiver employing the most advanced digital signal processing techniques in hardware to predict realizable error performances.

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In this paper altitude measurement from water surface using laser beam is presented. Research data indicate that the reflection of infrared waves from water surface is about zero and it is less than 2% for visible radiations. Phase-shift and heterodyne technique was used for the measurement, and the laser beam ( mW p nm 10 , 700 = = l ) was modulated by a sine wave having a fixed frequency. The optimum design and low-noise elements made it possible to detect a light power about 20 nW at operating frequency.

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In this paper a new method for determining the search area for motion estimation algorithm based on block matching is suggested. In the proposed method the search area is adaptively found for each block of a frame. This search area is similar to that of the full search (FS) algorithm but smaller for most blocks of a frame. Therefore, the proposed algorithm is analogous to FS in terms of regularity but has much less computational complexity. To find the search area, the temporal and spatial correlations among the motion vectors of blocks are used. Based on this, the matched block is chosen from a rectangular area that the prediction vectors set out. Simulation results indicate that the speed of the proposed algorithm is at least 7 times better than the FS algorithm.

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Electric power restructuring offers a major change to the vertically integrated monopoly. The change manifests the main part of engineers’ efforts to reshape the three components of today’s vertically integrated monopoly: generation, distribution and transmission. In a restructured environment, the main tasks of these three components will remain the same as before, however, to comply with FERC orders, new types of unbundling, coordination and rules are to be established to guarantee competition and non-discriminatory open access to all users. This paper provides the generation schedule of a GENCO in a deregulated power system. It is shown that the goal of generation schedule in the new structure is different from the traditional centralized power systems. The modeling of generation scheduling problem in a competitive environment is demonstrated by taking into account the main purposes of GENCOs which are selling electricity as much as possible and making higher profit. The GENCOs of an area are introduced via a model whose objective function consists of hourly spot market price as income and different kinds of costs. The constraints are the general ones of such a problem e.g. minimum up/down time, minimum and maximum generation and ramp rate. Using one of the classical optimization methods, the hourly generation schedule of the generating units will be obtained in this competitive environment. The results of this section will be used by ISO. The ISO will finalize the schedules of GENCOs by taking into account the technical considerations like the power flow of transmission lines. The model and the optimization methods are implemented on IEEE-RTS benchmark with 24 buses and 32 generating units.

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Developing a mathematical model for the artificial generation of electrocardiogram (ECG) signals is a subject that has been widely investigated. One of its uses is for the assessment of diagnostic ECG signal processing devices. So the model should have the capability of producing a wide range of ECG signals, with all the nuances that reflect the sickness to which humans are prone, and this would necessarily include variations in heart rate variability (HRV). In this paper we present a comprehensive model for generating such artificial ECG signals. We incorporate into our model the effects of respiratory sinus arrhythmia, Mayer waves and the important very low frequency component in the power spectrum of HRV. We use the new modified Zeeman model for generating the time series for HRV, and a single cycle of ECG is produced using a radial basis function neural network.

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A modified circular patch antenna design has been proposed in this paper, the bandwidth of this antenna is optimized using the genetic algorithm (GA) based on fuzzy decision-making. This design is simulated with HP HFSS Program that based on finite element method. This method is employed for analysis at the frequency band of 1.4 GHz- 2.6 GHz. It gives good impedance bandwidth of the order of 15.5% at the frequency band of 1.67GHz- 1.95GHz and 10.6% at 2.23GHz- 2.48GHz. It means that impedance bandwidth increases above 4.9% than the impedance bandwidth of ordinary circular patch antennas and band width rise from 1.78GHz- 1.98GHz (10.6%) to 1.67GHz- 1.95GHz (15.5%) and 2.23GHz- 2.48GHz (10.6%). The antenna fabricated with two slots on circular patch antenna. The measured results of the optimized antenna validate a high compatibility between the simulation and the measurements.

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The concepts of robust classification and intelligently controlling the search process of genetic algorithm (GA) are introduced and integrated with a conventional genetic classifier for development of a new version of it, which is called Intelligent and Robust GA-classifier (IRGA-classifier). It can efficiently approximate the decision hyperplanes in the feature space. It is shown experimentally that the proposed IRGA-classifier has removed two important weak points of the conventional GA-classifiers. These problems are the large number of training points and the large number of iterations to achieve a comparable performance with the Bayes classifier, which is an optimal conventional classifier. Three examples have been chosen to compare the performance of designed IRGA-classifier to conventional GA-classifier and Bayes classifier. They are the Iris data classification, the Wine data classification, and radar targets classification from backscattered signals. The results show clearly a considerable improvement for the performance of IRGA-classifier compared with a conventional GA-classifier.

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Multi-constraint quality-of-service routing will become increasingly important as the Internet evolves to support real-time services. It is well known however, that optimum multi-constraint QoS routing is computationally complex, and for this reason various heuristics have been proposed for routing in practical situations. Among these methods, those that use a single mixed metric are the most popular. Although mixed metric routing discards potentially useful information, this is compensated for by significantly reduced complexity. Exploiting this tradeoff is becoming increasingly important where low complexity designs are desired, such as in battery operated wireless applications. In this paper, a novel single mixed metric multi-constraint routing algorithm is introduced. The proposed technique has similar complexity compared with existing low complexity methods. Simulation results are presented which show that it can obtain better performance than comparable techniques in terms of generating feasible multi-constraint QoS routes.

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Restructuring of power system has faced this industry with numerous uncertainties. As a result, transmission expansion planning (TEP) like many other problems has become a very challenging problem in such systems. Due to these changes, various approaches have been proposed for TEP in the new environment. In this paper a new algorithm for TEP is presented. The method is based on probabilistic locational marginal price (LMP) considering electrical loss, transmission tariffs, and transmission congestion costs. It also considers the load curtailment cost in LMP calculations. Furthermore, to emphasize on competence of competition ability of the system, the final plan(s) is (are) selected based on minimization of average of total congestion cost for transmission system.

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Microarray technology is a new and powerful tool for concurrent monitoring of large number of genes expressions. Each microarray experiment produces hundreds of images. Each digital image requires a large storage space. Hence, real-time processing of these images and transmission of them necessitates efficient and custom-made lossless compression schemes. In this paper, we offer a new architecture for lossless compression of microarray images. In this architecture, we have used a dedicated hardware for separation of foreground pixels from the background ones. By separating these pixels and using pipeline architecture, a higher lossless compression ratio has been achieved as compared to other existing methods

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Fibrillation is a hazardous phenomenon in cardiac muscle and so any new work towards the understanding of this process is important to the development of new methods in diagnosis and therapy. In this work we have used surface and intra cardiac ECGs of patients with chronic atrial fibrillation (AF). By means of the blind source separation (BSS) algorithm, which is a well-known method in signal processing, the AF process has been deconstructed into its independent components and we can show that from the point of view of these components the surface ECGs contain the same information as the intra atria electrogram. Then the important components have been related to the ionic currents of the cell. We show that one of these independent components can be influenced by the sodiumcalcium exchange current, (iNaCa) and hence by controlling iNaCa we may be able to control the fibrillation process. This new idea can bring about new strategies in drug therapy.

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The mixed-signal circuits with both analog and digital blocks on a single chip have wide applications in communication and RF circuits. Integrating these two blocks can cause serious problems especially in applications requiring fast digital circuits and high performance analog blocks. Fast switching in digital blocks generates a noise which can be introduced to analog circuits by the common substrate. This noise can decrease the performance of mixed-signal circuits therefore, studying this noise and the way it is transmitted will lead to solutions for reducing it and improving mixed-signal circuit’s performance. In this paper, an efficient model for substrate is extracted from Green’s function in MATLAB environment, and its accuracy is demonstrated. Using a VCO and a multiplier as analog and digital blocks, respectively and simulating them along with the proposed model of the substrate, the effects of substrate noise coupled to analog blocks are shown. Finally, some methods for reducing this noise are applied to the circuit, and the results are compared to each other. The results indicate that using P+ Guard Rings is the best method for reducing substrate noise in the mixed-signal circuits.

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A direct conversion modulator-demodulator with even harmonic mixers with emphasis on noise analysis is presented. The circuits consist of even harmonic mixers (EHMs) realized with antiparallel diode pairs (APDPs). We evaluate the different levels of I/Q imbalances and DC offsets and use signal space concepts to analyze the bit error rate (BER) of the proposed transceiver using M-ary QAM schemes. Moreover, the simultaneous analysis of the signal and noise has been presented.

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Power transformers are key components in electrical power supplies and their failure could cause severe consequences on continuity of service and also generates substantial costs. Identifying problems at an early stage, before catastrophic failure occurs, is a great benefit for reliable operation of power transformers. Frequency Response Analysis (FRA) is a new, well-known and powerful diagnostic test technique for transformers which could find mechanical as well as electrical faults such as detection and positioning of winding short circuit, winding movement, loss of clamping pressure, aging of insulation, etc. Yet there are several practical limitations to affect the accuracy and ease using this test as a regular condition monitoring technique in the field that many of them originated from noise and measuring errors. This paper purposes a transformer automated self diagnosis system can be installed on every power supply as a part of SCADA to extract FRA graphs from transformers and offers high repeatability which is a great benefit for FRA test. This is the first time that KALMAN Filter will be use in order to eliminate narrow-band and wide-band noises from FRA graphs that ends up not only smoothed measurement but also rate of changes that is so valuable in decision making and scheduling for transformers maintenance. So we will have an intelligent system which is able to predict the future of transformer using experience of not only own self but also all the transformers in an integrated network.

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In this paper a hybrid active DC line conditioner for fluctuations and ripples reduction in voltage and current of DC power systems is proposed. Malfunctions in operation of equipments and systems which are supplied by low quality distribution power systems are one of the main effects of DC voltage ripple. In the proposed configuration a hybrid system including series and shunt active line conditioners for ripple reduction of load voltage and source current is used. Simulation and experimental results are provided to show the performance of the proposed configuration in different states.

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The development of numerical techniques now permits us to analyze complex structures such as dielectric resonator filters and planar passive elements for coplanar monolithic microwave integrated circuits. In this paper, we describe a novel method for designing dielectric resonator filters. Then a Chebychev band pass filter is designed by coaxially placing high-Q TM01Q dielectric resonators in a cutoff circular waveguide. In the present work, discussions are made regarding high-Q resonators and inter-resonator coupling.

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Medium-term modeling of electricity market has essential role in generation expansion planning. On the other hand, uncertainties strongly affect modeling and consequently, strategic analysis of generation firms in the medium term. Therefore, models considering these uncertainties are highly required. Among uncertain variables considered in the medium term generation planning, demand and hydro inflows are of the greatest importance. This paper proposes a new approach for simulating the operation of power market in medium-term, taking into account demand and hydro inflows uncertainties. The demand uncertainty is considered using Monte-Carlo simulations. Standard Deviation over Expected Profit (SDEP) of generation firms based on simulation results is introduced as a new index for analyzing the influence of the demand uncertainty on the behavior of market players. The correlation between capacity share of market players and their SDEP is also demonstrated. The uncertainty of inflow as a stochastic variable is dealt using scenario tree representation. Rational uncertainties as strategic behavior of generation firms, intending to maximize their expected profit, is considered and Nash-Equilibrium is determined using the Cournot model game. Market power mitigation effects through financial bilateral contracts as well as demand elasticity are also investigated. Case studies confirm that this representation of electricity market provides robust decisions and precise information about electricity market for market players which can be used in the generation expansion planning framework.

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Contrast resolution and detail resolution are two important parameters in ultrasound imaging. This paper presents a new method to enhance these parameters, simultaneously. A parallel auxiliary beamformer has been employed whose weightings are such that an estimation of the leaked signal through the main beamformer is obtained. Then the output of main beamformer is modified according to the estimated leaked signal. The efficiency of our adaptive method is demonstrated by applying it over an experimental data set and provided an enhancement of about 22 percent in lateral resolution and 15-20 dB in contrast resolution. This method also has the advantages of simplicity and possibility of real time implementation.

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In this paper, the performance of a Ring Laser Gyro based inertial navigation is investigated. Dynamic and stochastic modeling are applied to gyro simulation and performance evaluation. In the dynamic model, some parameters such as scale factor and environmental sensitivity have been determined, whereas in the stochastic model, the other parameters such as random drift and measurement noise have been computed. The performance of the system is evaluated for several inputs. Also, the parameter variation of output noise as a result of changing the dither characteristics is analyzed.