Showing 4 results for Sedghi
Shayegh, Mohammadi, Abdipour, Sedghi, Mirzavand,
Volume 2, Issue 1 (January 2006)
Abstract
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.
Mahdi Sedghi, Masoud Aliakbar-Golkar,
Volume 5, Issue 2 (June 2009)
Abstract
Optimal expansion of medium-voltage power networks is a common issue in electrical distribution planning. Minimizing total cost of the objective function with technical constraints and reliability limits, make it a combinatorial problem which should be solved by optimization algorithms. This paper presents a new hybrid simulated annealing and tabu search algorithm for distribution network expansion problem. Proposed hybrid algorithm is based on tabu search and an auxiliary simulated annealing algorithm controls the tabu list of the main algorithm. Also, another auxiliary simulated annealing based algorithm has been added to local searches of the main algorithm to make it more efficient. The numerical results show that the method is very accurate and fast comparing with the other algorithms.
Saba Sedghizadeh , Caro Lucas , Hassan Ghafoori Fard ,
Volume 5, Issue 2 (June 2009)
Abstract
An adaptive online flux-linkage estimation method for the sensorless control of switched reluctance motor (SRM) drive is presented in this paper. Sensorless operation is achieved through a binary observer based algorithm. In order to avoid using the look up tables of motor characteristics, which makes the system, depends on motor parameters, an adaptive identification algorithm is used to estimate of the nonlinear flux-linkage parameters. This method makes position and speed estimation more accurate and robust towards any model uncertainty, also it is suitable replacement for a priori knowledge of motor characteristics.
S. Tannaz, T. Sedghi,
Volume 14, Issue 2 (June 2018)
Abstract
In this article, a fabulous method for database retrieval is proposed. The multi-resolution modified wavelet transform for each of image is computed and the standard deviation and average are utilized as the textural features. Then, the proposed modified bit-based color histogram and edge detectors were utilized to define the high level features. A feedback-based dynamic weighting of shape, color and textural features composition produce a resistant feature vectors for image retrieval and recall. A comprehensive and unified matching scheme based on matrix error rate technique was accomplished for similarity of image and retrieval procedure. The feature vectors size in our algorithm is the least one evaluated to the different techniques. Furthermore, the calculation time of previously published techniques is much more than the presented algorithm which is a benefit in proposed retrieval method. The experimental results illustrates that novel algorithm obtains more precious in retrieval and the efficiency in evaluating with the other techniques and algorithms at Corel color image database.
