Iranian Journal of Electrical and Electronic Engineering
Volume:7 Issue: 2, Jun 2011

The paper addresses a new QRS complex geometrical feature extractiontechnique as well as its application for electrocardiogram (ECG) supervised hybrid (fusion)beat-type classification. To this end, after detection and delineation of the major events of ECG signal via a robust algorithm, each QRS region and also its corresponding discretewavelet transform (DWT) are supposed as virtual images and each of them is divided intoeight polar sectors. Then, the curve length of each excerpted segment is calculated and is used as the element of the feature space. To increase the robustness of the proposedclassification algorithm versus noise, artifacts and arrhythmic outliers, a fusion structureconsisting of three Multi Layer Perceptron-Back Propagation (MLP-BP) neural networkswith different topologies and one Adaptive Network Fuzzy Inference System (ANFIS)were designed and implemented. To show the merit of the new proposed algorithm, it was applied to all MIT-BIH Arrhythmia Database records and the discrimination power of the classifier in isolation of different beat types of each record was assessed and as the result,the average accuracy value Acc=98.27% was obtained. Also, the proposed method wasapplied to 8 number of arrhythmias (Normal, LBBB, RBBB, PVC, APB, VE, PB, VF)belonging to 19 number of the aforementioned database and the average value ofAcc=98.08% was achieved. To evaluate performance quality of the new proposed hybridlearning machine, the obtained results were compared with similar peer-reviewed studies in this area.

Two-dimensional (2D) adaptive filtering is a technique that can be applied tomany image and signal processing applications. This paper extends the one-dimensionaladaptive filter algorithms to 2D structure and the novel 2D adaptive filters are established.Based on this extension, the 2D variable step-size normalized least mean squares (2D-VSSNLMS),the 2D-VSS affine projection algorithms (2D-VSS-APA), the 2D set-membershipNLMS (2D-SM-NLMS), the 2D-SM-APA, the 2D selective partial update NLMS (2DSPU-NLMS), and the 2D-SPU-APA are presented. In 2D-VSS adaptive filters, the stepsizechanges during the adaptation which leads to improve the performance of thealgorithms. In 2D-SM adaptive filter algorithms, the filter coefficients are not updated ateach iteration. Therefore, the computational complexity is reduced. In 2D-SPU adaptivealgorithms, the filter coefficients are partially updated which reduce the computationalcomplexity. We demonstrate the good performance of the proposed algorithms thoroughseveral simulation results in 2D adaptive noise cancellation (2D-ANC) for imagedenoising. The results are compared with the classical 2D adaptive filters such as 2D-LMS,2D-NLMS, and 2D-APA.

The role of waveform design is central to effective radar resource managementfor state-of-the art radar systems. The waveform shape employed by any radar system hasalways been a key factor in determining the performance and application. The design ofradar waveform to minimize mean square error (MMSE) in estimating the target impulseresponse is based on power allocation using waterfilling. This paper shows the effect ofvarious power control strategies in the MMSE performance of the waveform design. Wefind that the truncated power control strategy exhibits a good MMSE performance. Theperformance improvement results from the fact that with the truncated power control nopower is wasted in poor quality modes.

With the explosive growth in portable computing and wireless communicationduring last few years, power dissipation has become critical issue. Under such conditiongate leakage has been recognized as a dominant component of power dissipation. Thiswork proposes a modified hybrid MOSFET (MHMOS) i.e. gate-to-source/drain nonoverlapMOSFET in combination with high-k layer/interfacial oxide as gate stack to reducethe gate leakage current. The extended S/D in the non-overlap region is induced by fringing gate electric field through high-k dielectric and SiO2 dual spacer. Compact analytical model and Sentaurus simulation have been used to study the gate leakage behaviour of MHMOS. A good agreement is observed between analytical and Sentaurus simulation results. It is found that MHMOS structure has reduced the gate leakage current to great extent as compared to conventional overlapped MOSFET structure. Further, degradation in drive current caused by the utilization of high-k gate dielectric has been improved by the use of dual spacer.

In this paper, we report the simulation results for impact of nonlinear Kerr effecton band structures of a two dimensional photonic crystal (2D-PhC) with no defect, a PhCbased W1-waveguide (W1W), and also Coupled-Cavity Waveguides (CCWs). All PhCstructures are assumed to a square lattice of constant a made of GaAs rods of radius r=0.2a,in an air background. The numerical simulation was performed using the nonlinear finitedifference time domain (NFDTD) technique. In doing so, we have normalized the electricfield and the electric flux density vectors, and used a multi probe procedure. These haveresulted in very accurate dispersion relations that, in turn, have enabled us to make somenovel observations. For instance, simulations show that with an increase in the input lightintensity (in the nonlinear regime) the band edges for all three PhC structures experiencesome red shifts. The red shifts observed for CCWs are, of course, larger than the red shifts experienced by other two structures. Furthermore, the numerical results for CCWs also show that the larger the light input intensity, the smaller the corresponding maximum light group velocity becomes. To the best of our knowledge, this is the first instance that such observations on the impact of the nonlinear Kerr effect on the band diagram of 2D-PhC waveguides are reported.

Voltage instability is a major threat for security of power systems. Preservingvoltage stability margin at a certain limit is a vital requirement for today’s power systems.Assessment of voltage stability margin is a challenging task demanding sophisticatedindices. In this paper, for the purpose of on line voltage stability assessment a new indexbased on the correlation characteristic of network voltage profile is proposed. Voltageprofile comprising all bus voltages contains the effect of network topoloy, load-generationpatterns and reactive power compensation on the system behavior and voltage stabilitymargin. Therefore, the proposed index is capable to clearly reveal the effect of all systemcharacteristics and events on the voltage stability margin. The most attractive feature forthis index is its fast and easy calculation from synchronously measured voltage profilewithout any need to system modeling and simulation and without any dependency onnetwork size. At any instant of system operation by merely measuring network voltageprofile and no further simulation calculation this index could be evaluated with respect to aspecific reference profile. The results show that the behavior of this index with respect tothe change in system security is independent of the selected reference profile. Thesimplicity and easy calculation make this index very suitable for on line application. Theproposed approach has been demonstrated on IEEE 39 bus test system with promisingresults showing its effectiveness and applicability.

Bayesian Networks (BN) provides a robust probabilistic method of reasoningunder uncertainty. They have been successfully applied in a variety of real-world tasks butthey have received little attention in the area of load-frequency control (LFC). In practice,LFC systems use proportional-integral controllers. However since these controllers aredesigned using a linear model, the nonlinearities of the system are not accounted for andthey are incapable to gain good dynamical performance for a wide range of operatingconditions in a multi-area power system. A strategy for solving this problem due to thedistributed nature of a multi-area power system, is presented by using a BN multi-agentsystem. This method admits considerable flexibility in defining the control objective. AlsoBN provides a flexible means of representing and reasoning with probabilistic information.Efficient probabilistic inference algorithms in BN permit answering various probabilisticqueries about the system. Moreover using multi-agent structure in the proposed model,realized parallel computation and leading to a high degree of scalability. To demonstratethe capability of the proposed control structure, we construct a BN on the basis ofoptimized data using genetic algorithm (GA) for LFC of a three-area power system withtwo scenarios.