Iranian Journal of Electrical and Electronic Engineering
Volume:10 Issue: 3, Sep 2014

The proposed theorem in this paper is indicative of a kind of duality in the propagation of waves in the dual media of and in the spherical structures. Independent of wave frequency, the number of layers, their thickness, and the type of polarization, this theorem holds true in case of any change in any of these conditions. Theorem: Consider a plane wave incident on a multilayered spherical structure. The core of structure may be PEC, metamaterial or dielectric. If we apply the interchange or for the constituting materials of the spherical structure and the surrounding medium the radar cross section of the structure will not change in any direction.

Gaussian Mixture Models (GMMs) of power spectral densities of speech and noise are used with explicit Bayesian estimations in Wiener filtering of noisy speech. No assumption is made on the nature or stationarity of the noise. No voice activity detection (VAD) or any other means is employed to estimate the input SNR. The GMM mean vectors are used to form sets of over-determined system of equations whose solutions lead to the first estimates of speech and noise power spectra. The noise source is also identified and the input SNR estimated in this first step. These first estimates are then refined using approximate but explicit MMSE and MAP estimation formulations. The refined estimates are then used in a Wiener filter to reduce noise and enhance the noisy speech. The proposed schemes show good results. Nevertheless, it is shown that the MAP explicit solution, introduced here for the first time, reduces the computation time to less than one third with a slight higher improvement in SNR and PESQ score and also less distortion in comparison to the MMSE solution.

One of the related problems of OCR systems is discrimination of fonts in machine printed document images. This task improves performance of general OCR systems. Proposed methods in this paper are based on various fractal dimensions for font discrimination. First, some predefined fractal dimensions were combined with directional methods to enhance font differentiation. Then, a novel fractal dimension was introduced in this paper for the first time. Our feature extraction methods which consider font recognition as texture identification are independent of document content. Experimental results on different pages written by several font types show that fractal geometry can overcome the complexities of font recognition problem.

Sending compressed video data in error-prone environments (like the Internet and wireless networks) might cause data degradation. Error concealment techniques try to conceal the received data in the decoder side. In this paper, an adaptive boundary matching algorithm is presented for recovering the damaged motion vectors (MVs). This algorithm uses an outer boundary matching or directional temporal boundary matching method to compare every boundary of candidate macroblocks (MBs), adaptively. It gives a specific weight according to the accuracy of each boundary of the damaged MB. Moreover, if each of the adjacent MBs is already concealed, different weights are given to the boundaries. Finally, the MV with minimum adaptive boundary distortion is selected as the MV of the damaged MB. Experimental results show that the proposed algorithm can improve both objective and subjective quality of reconstructed frames without any considerable computational complexity; The average PSNR in some frames of test sequences increases about 4.59, 4.44, 3.57, and 2.98 dB compared to classic boundary matching, directional boundary matching, directional temporal boundary matching, and outer boundary matching algorithm, respectively.

This paper proposes a new bilateral control scheme to ensure both transparency and robust stability under unknown constant time delay in stiff environment. Furthermore, this method guaranties suitable performance and robust stability when transition occurs between soft and stiff environments. This framework is composed of an adaptive sliding mode controller and an adaptive impedance controller, where online estimation of the environment impedance is performed, and then used as the desired impedance at the master side. Numerical simulations are provided to verify the theoretical results under different conditions, such as constant and time-varying delay, obstructed environment and transitioning between soft and stiff environment. Afterwards, comparison with a recent work is addressed.

Static Synchronous Series Compensator (SSSC) is a series compensating Flexible AC Transmission System (FACTS) controller for maintaining to the power flow control on a transmission line by injecting a voltage in quadrature with the line current and in series mode with the line. In this work, an Adaptive Network-based Fuzzy Inference System controller (ANFISC) has been proposed for controlling of the SSSC-based damping system and applied to a Single Machine Infinite Bus (SMIB) power system. For implementation of the learning process in this controller, we use of the one approach of the learning ability that named as Forward Signal and Backward Error Back-Propagation (FSBEBP) method for improving of the system efficiency. This artificial intelligence-based control model leads to a controller with adaptive structure, improved correctness, high damping ability and dynamic performance. System implementation is easy and it requires 49 fuzzy rules for inference engine of the system. As compared with the other complex neuro-fuzzy systems, this controller has medium number of the fuzzy rules and low number of layers, but it has high accuracy. In order to demonstrate of the proposed controller ability, it is simulated and its output compared with that of classic Lead-Lag-based Controller (LLC) and PI controller.

The main goal of this paper is to study statistical indices and evaluate AGC indices in power system which has large penetration of the WTGs. Increasing penetration of wind turbine generations, needs to study more about impacts of it on power system frequency control. Frequency control is changed with unbalancing real-time system generation and load. Also wind turbine generations have more fluctuations and make system more unbalance. Then AGC loop helps to adjust system frequency and the scheduled tie-line powers. The quality of AGC loop is measured by some indices. A good index is a proper measure shows the AGC performance just as the power system operates. One of well-known measures in literature which was introduced by NERC is Control Performance Standards(CPS). Previously it is claimed that a key factor in CPS index is related to standard deviation of generation error, installed power and frequency response. This paper focuses on impact of a several hours-ahead wind speed forecast error on this factor. Furthermore evaluation of conventional control performances in the power systems with large-scale wind turbine penetration is studied. Effects of wind speed standard deviation and also degree of wind farm penetration are analyzed and importance of mentioned factor are criticized. In addition, influence of mean wind speed forecast error on this factor is investigated. The study system is a two area system which there is significant wind farm in one of those. The results show that mean wind speed forecast error has considerable effect on AGC performance while the mentioned key factor is insensitive to this mean error.

In this paper, the Vector Based Swarm Optimization method is used for designing an optimal controller for the maximum power point tracker of a stand-alone PV System. The proposed algorithm is executed on vectors in a multi-dimension vector space. These vectors by appropriated orientation converge to a global optimum while the algorithm runs. The Remarkable point of the VBSO algorithm is how using completely random coefficients have good influence on algorithm performance. The generated energy is delivered to a boost converter including a resistive load. The duty cycle of the converter’s switch is determined in order to minimize generated power deviation, relative to PV voltage.

This paper considers a new switched reluctance motor (SRM) structure aiming at high starting torque with low volume. For some applications such as EVs (Electrical Vehicles), the motor volume and starting torque is a critical point in its design. In many methods, reducing the motor volume causes reduction in starting torque and decreases the motor efficiency. Unlike conventional SRMs, the rotor pole is skewed in the proposed structure along the motor axis. An approximated two-dimensional finite element method (FEM) is used to speed up computational time and some comparisons with three-dimensional FEM are considered for more reliability. Final results show the efficiency of the proposed structure.

In this paper, one-cycle control (OCC), as a constant-frequency PWM control strategy for current control of a six-switch brushless dc (BLDC) motor drive is investigated. Developed current regulator is a unified controller and PWM modulator. Employing the one-cycle control strategy, decreases the torque ripple resulted from the conventional hysteresis current controllers and therefore, the vibration and acoustic noise of the drive are reduced. Total operations of the system control and OCC strategy are realized by a low-cost general-purpose AVR microcontroller (Atmega8) that leads to a low-cost, high performance BLDC motor drive. Computer simulations using Matlab simulator, have been presented to show the good characteristics of this solution. Furthermore, experimental works show the excellent behavior of developed BLDC drive and agreement with simulation results.