Iranian Journal of Electrical and Electronic Engineering
Volume:7 Issue: 1, Mar 2011

In this study, a new long-duration holter electrocardiogram (ECG) major events detection-delineation algorithm is described which operates based on the false-alarm error bounded segmentation of a decision statistic with simple mathematical origin. To meet this end, first three-lead holter data is pre-processed by implementation of an appropriate bandpass finite-duration impulse response (FIR) filter and also by calculation of the Euclidean norm between corresponding samples of three leads. Then, a trous discrete wavelet transform (DWT) is applied to the resulted norm and an unscented synthetic measure is calculated between some obtained dyadic scales to magnify the effects of low-power waves such as P or T-waves during occurrence of arrhythmia(s). Afterwards, a uniform length window is slid sample to sample on the synthetic scale and in each slid, six features namely as summation of the nonlinearly amplified Hilbert transform, summation of absolute first order differentiation, summation of absolute second order differentiation, curve length, area and variance of the excerpted segment are calculated. Then all feature trends are normalized and superimposed to yield the newly defined multiple-order derivative wavelet based measure (MDWM) for the detection and delineation of ECG events. In the next step, a α-level Neyman-Pearson classifier (which is a false-alarm probability-FAP controlled tester) is implemented to detect and delineate QRS complexes. To show advantages of the presented method, it is applied to MIT-BIH Arrhythmia Database, QT Database, and T-Wave Alternans Database and as a result, the average values of sensitivity and positive predictivity Se = 99.96% and P+ = 99.96% are obtained for the detection of QRS complexes, with the average maximum delineation error of 5.7 msec, 3.8 msec and 6.1 msec for P-wave, QRS complex and T-wave, respectively showing marginal improvement of detection-delineation performance. In the next step, the proposed method is applied to DAY hospital high resolution holter data (more than 1,500,000 beats including Bundle Branch Blocks-BBB, Premature Ventricular Complex-PVC and Premature Atrial Complex-PAC) and average values of Se=99.98% and P+=99.97% are obtained for QRS detection. In summary, marginal performance improvement of ECG events detection-delineation process in a widespread values of signal to noise ratio (SNR), reliable robustness against strong noise, artifacts and probable severe arrhythmia(s) of high resolution holter data and the processing speed 163,000 samples/sec can be mentioned as important merits and capabilities of the proposed algorithm.

This paper presents a new method called vespiary regular hexagonal (VRH) model in order to calculate parasitic capacitance between conductor wire filaments of one turn of coil (OTC) and between conductor wire filaments and liner and also total capacitance of one turn of the helix magneto flux cumulative generator (MCG) coil include single-layer conductor wire filaments in form of rectangular cross-section. In this paper, wire filaments of the coil are separated into many very small similar elementary cells. In this structure, an equilateral lozenge-shape basic cell (ELBC) with two trapezium-shape regions is considered between two adjacent conductor wire filaments in one turn of the generator coil. This method applies to calculate stray capacitance of one turn of the coil with multi conductor wire filaments (CWFs).

We present an optimized design for GaAs/AlGaAs quantum cascade lasers operating at ‎‎4.1THz. This was based on a three-well active module with diagonal radiative transition. This ‎was performed by modifying the existing model structure, to reduce the parasitic anticrossings ‎‎(leakage currents) as well as the optical gain linewidth. While the gain FWHM was reduced by ‎more than 50% the gain peak was increased by about 23.3%.‎

This paper presents a new approach for estimating and improving voltage stability margin from phase and magnitude profile of bus voltages using sensitivity analysis of Voltage Stability Assessment Neural Network (VSANN). Bus voltage profile contains useful information about system stability margin including the effect of load-generation, line outage and reactive power compensation so, it is adopted as input pattern for VSANN. In fact, VSANN establishes a functionality for VSM with respect to voltage profile. Sensitivity analysis of VSM with respect to voltage profile and reactive power compensation extracted from information stored in the weighting factor of VSANN, is the most dominant feature of the proposed approach. Sensitivity of VSM helps one to select most effective buses for reactive power compensation aimed enhancing VSM. The proposed approach has been applied on IEEE 39-bus test system which demonstrated applicability of the proposed approach.

This paper consist of two sections: control and stabilizing approach for chaotic behaviour of converter is introduced in first section of this paper for the removal of harmonic caused by the chaotic behaviour in current converter. For this work, a Time- Delayed Feedback Controller (TDFC) control method for stability chaotic behaviour of buck converter for switching courses in current control mode is presented. This behaviour is demonstrated by presenting a piecewise linear discrete map for this converter and then combining the feedback equation to obtain the overall equation of the converter. A simple time-delay feedback control method is applied to stabilize the Unstable Periodic Orbits (UPOs). In second section is studied the effect of a parallel metal oxide surge arrester on the ferroresonance oscillations of the transformer. It is expected that the arresters generally cause ferroresonance drop out. Simulation has been done on a three phase power transformer with one open phase. Effect of varying input voltage has been studied. The simulation results reveal that connecting the arrester to the transformer poles, exhibits a great mitigating effect on ferroresonant over voltages. Phase plane along with bifurcation diagrams are also presented. Significant effect on the onset of chaos, the range of parameter values that may lead to chaos and magnitude of ferroresonant voltages has been obtained, shown and tabulated.

The design process of a superconducting current limiter (SFCL) requires simulation and definition of its electrical, magnetic and thermal properties in form of equivalent circuits and mathematical models. However, any change in SFCL parameters: dimension, resistance, and operating temperature can affect the limiting mode, quench time, and restore time. In this paper, following the simulation of electrical and thermal behavior of resistive and inductive SFCLs and investigation on their performance variation responded to change parameters, the best design cases will be selected by using multiple criteria decision making (MCDM) techniques. As a case study, to evaluate proposed MCDM approaches in design of superconducting fault current limiter, a model in which a SFCL is located at an outgoing feeder in a 20 kV distribution substation will be considered and best designs will be presented for both resistive and inductive type.

This paper presents a method to control both the dc boost and the ac output voltage of Z-source inverter using neural network controllers. The capacitor voltage of Z-source network has been controlled linearly in order to improve the transient response of the dc boost control of the Z-source inverter. The peak value of the line to line ac output voltage is used to control and keep the ac output at its desired value. A modified space vector pulse-width-modulation method is also applied to control the shoot-through duty ratio for boosting dc voltage. This modified method lets the dc voltage stress across the inverter switches be minimized. The neural network control technique is verified by simulation results. The results are compared with that of the traditional PI controller.