2014
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THD Analysis in ClosedLoop Analog PWM ClassD Amplifiers
2
2
In this paper, we investigate the parameters affecting Total Harmonic Distortion (THD) and Power Supply Rejection Ratio (PSRR) in PWM Class D Amplifiers (CDAs) on the basis of linear models with feedback. From our mathematical analysis, we show that the THD of a PWM Class D amplifier with feedback can be improved by increasing the gain of the integrator through adding another amplifier at the output of the integrator. We also show that the THD can be further improved by means of two cascaded amplifiers with a single pole. We verify our analysis by means of PSPICE simulations. Simulation results show that the THD of the gain boosting and the two cascaded amplifiers with a single pole CDAs can be improved by as much as 1.4 times and 2 times, respectively.
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1
5


Parviz
Amiri
Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran.
Faculty of Electrical and Computer Engineering,
Iran


Mostafa
Kohestani
Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran.
Faculty of Electrical and Computer Engineering,
Iran


Mahmood
Seifouri
Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran.
Faculty of Electrical and Computer Engineering,
Iran
ClassD ampliﬁers
Audio ampliﬁers
Switching ampliﬁers
THD
Distortion
Pulse width modulation
ANewClosedformMathematicalApproachtoAchieve Minimum Phase Noise in Frequency Synthesizers
2
2
The aim of this paper is to minimize output phase noise for the pure signal synthesis in the frequency synthesizers. For this purpose, first, an exact mathematical model of phase locked loop (PLL) based frequency synthesizer is described and analyzed. Then, an exact closedform formula in terms of synthesizer bandwidth and total output phase noise is extracted. Based on this formula, the phase noise diagram as a function of bandwidth is plotted. From the analysis and simulation results, it is observed that the synthesizer has a minimum phase noise at a particular bandwidth.
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7
13


Sattar
SamadiGorji
Babol Nushirvani University of Technology, Department of Electrical Engineering, Babol, Iran
Babol Nushirvani University of Technology,
Iran


Bijan
Zakeri
Babol Nushirvani University of Technology, Department of Electrical Engineering, Babol, Iran
Babol Nushirvani University of Technology,
Iran


MohammadReza
Zahabi
Babol Nushirvani University of Technology, Department of Electrical Engineering, Babol, Iran
Babol Nushirvani University of Technology,
Iran
Frequency synthesizers
Phase noise
Phaselocked loop
Phase noise reduction
ControlStrategiesforPerformanceAssessmentofan Autonomous Wind Energy Conversion System
2
2
Renewable energy sources like wind, sun, and hydro are considered as a reliable alternative to the traditional energy sources such as oil, natural gas, or coal. This paper describes modeling and simulations to determine a method for the power performance evaluation of autonomous wind turbine system. A speed control regulator is utilized to control the DC bus voltage. The inverter gate’s signals are generated by decoding the Hall effect signals of the motor. The threephase output of the inverter is applied to the permanent magnet synchronous generator (PMSG) block's stator windings. This study shows that the use of resonant controllers ensures the stability of the threephase source supplying the load which may be unbalanced and subjected to abrupt variations. It also shows that use of PI controller ensures the regulation of DC bus to a reference voltage.
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15
20


MohammadReza
HojatyDana
Department of Electrical Engineering, Islamic Azad University Boroujerd Branch (IAUB), Lorestan, Iran
Department of Electrical Engineering, Islamic
Iran


MohammadReza
AlizadehPahlavani
Department of Electrical Engineering, MalekAshtar University of Technology (MUT), Tehran, Iran
Department of Electrical Engineering, MalekAshtar
Iran
Wind energy
Distributed generation
Voltage controller
PI controller
DALD:DistributedAsynchronousLocalDecontamination Algorithm in Arbitrary Graphs
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2
Network environments always can be invaded by intruder agents. In networks where nodes are performing some computations, intruder agents might contaminate some nodes. Therefore, problem of decontaminating a network infected by intruder agents is one of the major problems in these networks. In this paper, we present a distributed asynchronous local algorithm for decontaminating a network. In most of prior algorithms, there is a coordinator agent that starts from a node and decontaminates the network. Since this procedure is handled by an agent and in centralized mode decontamination algorithm is very slow. In our algorithm, the network is decomposed to some clusters and a coordinator is advocated to each cluster. Therefore, there is more than one coordinator that each of them starts from different nodes in the network and decontaminates network, independently. In this case, network is decontaminated faster. In addition, in previous works the upper bound of the number of moves and the number of cleaner agents required to decontaminate network are given only for networks with special structures such as ring or tori while our algorithm establishes these upper bounds on networks with arbitrary structure.
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21
27


Maryam
Rahmaninia
Department of Computer Engineering, Islamic Azad University, GhasrEShirin Branch, Kermanshah, Iran.
Department of Computer Engineering, Islamic
Iran


Elnaz
Bigdeli
Electrical Engineering and Computer Science, University of Ottawa, Ontario, Canada.
Electrical Engineering and Computer Science,
Iran


Manouchehr
Zaker
Mathematics and Computer Science Department, Institute for Advanced Studies in Basic Sciences, Zanjan, Iran.
Mathematics and Computer Science Department,
Iran
Network decontamination
Mobile agents
Distributed algorithm
Optimum Design of a SRM Using FEM and PSO
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2
Nowadays the use of the Switched Reluctance Motors (SRMs) has been considerably increased in various home and industrial applications. Despite of many advantages of this type of motors, such as simple structure, low cost, and high reliability, the main disadvantage of them is the generation of high torque pulsation. This paper presents a novel method to optimize a typical SRM such that the torque ripple reaches its minimum value. Meanwhile, the torque average and the motor efficiency become maximum. It is shown that the pole width to the pole pitch ratio, for both stator and rotor poles, have a great impact on the torque ripple and torque average. Finite Element Method (FEM) is used to obtain the torque ripple, the torque average and the motor efficiency for a large number of ratios. A functional relationship is developed between the input and the output parameters. Normalized summation of the torque ripple minus the torque average and the efficiency is considered to be the cost function, which must be minimized. Then, the Particle Swarm Optimization (PSO) is used to find the optimum ratio of pole width to pole pitch, for both stator and rotor. The optimum design is verified by FEM.
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35


Mehdi
Ranjkesh
Faculty of Engineering, University of Guilan, Rasht, Iran.
Faculty of Engineering, University of Guilan,
Iran


Esmael
FallahChoolabi
Faculty of Engineering, University of Guilan, Rasht, Iran.
Faculty of Engineering, University of Guilan,
Iran


Mojtaba
Pourjafari
Faculty of Engineering, University of Guilan, Rasht, Iran
Faculty of Engineering, University of Guilan,
Iran
Switched Reluctance Motor(SRM)
Finite Element Method (FEM)
Particle Swarm Optimization (PSO)
The Application of MultiLayer Artificial Neural Networks in Speckle Reduction (Methodology)
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Optical Coherence Tomography (OCT) uses the spatial and temporal coherence properties of optical waves backscattered from a tissue sample to form an image. An inherent characteristic of coherent imaging is the presence of speckle noise. In this study we use a new ensemble framework which is a combination of several MultiLayer Perceptron (MLP) neural networks to denoise OCT images. The noise is modeled using Rayleigh distribution with the noise parameter, sigma, estimated by the ensemble framework. The input to the framework is a set of intensity and wavelet statistical features computed from the input image, and the output is the estimated sigma value for the noise model. In this article the methodology of this technique is explained.
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42


Mohammad R.
Pishgoo
Digital Communications Signal Processing (DCSP) Research Lab., Faculty of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University (SRTTU), Tehran, Iran.
Digital Communications Signal Processing
Iran


Mohammad R.
N. Avanaki
Department of Biomedical Engineering, College of Engineering and School of Medicine, Wayne State University, Detroit, MI 48201, USA
Department of Biomedical Engineering, College
Iran


Reza
Ebrahimpour
Brain& Intelligent Systems Research Lab., Department of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran
Brain& Intelligent Systems Research Lab.,
Iran
Optical Coherence Tomography (OCT)
Speckle redaction
Neural network
MultiLayer Perceptron
Mean Squared Error (MSE)