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A non-linear neural D/A converter for direct digital frequency synthesizers
, Article International Joint Conference on Neural Networks 2006, IJCNN '06, Vancouver, BC, 16 July 2006 through 21 July 2006 ; 2006 , Pages 2669-2672 ; 10987576 (ISSN); 0780394909 (ISBN); 9780780394902 (ISBN) ; Sedighi, B ; Sharif University of Technology
Institute of Electrical and Electronics Engineers Inc
2006
Abstract
In this paper, a new non-linear D/A converter (DAC) is presented. This D/A converter uses neural network to approximate a sine function. It is targeted for direct digital frequency synthesizers in which the phase to sine amplitude conversion is usually performed using a ROM. Utilizing the proposed DAC, the power hungry ROM is removed. A design example is presented and the performance of the DAC is compared to the conventional method. The impact of non-idealities on the performance of the system is also investigated. © 2006 IEEE
Generation of Endurance Time Excitation Functions using Wavelet Transform and Heuristic Optimization Methods
, Ph.D. Dissertation Sharif University of Technology ; Vafai, Abolhassan (Supervisor) ; Esmaeil Purestekanchi, Homayoon (Supervisor)
Abstract
Endurance Time (ET) method is a dynamic analysis in which structures are subjected to intensifying acceleration time histories. These excitations are also called Endurance Time Excitation Functions (ETEF). The reliability and accuracy of the ET method heavily depends on the accuracy of ETEFs. ETEFs are generated so that ETEFs dynamic characteristics must be consistent with dynamic characteristics of real ground motions. Since the number of ETEFs equations are considerably more than variables noninear optimization is used to generate ETEFs. In order to improve the accuracy of ETEFs two approaches can be used. First, modifying the objective function equations by considering more dynamic...