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Proceedings Paper

Neural network design approach for equiripple FIR digital filters
Author(s): Xiaohua Wang; Yigang He; Shaosheng Fan; Hong Li
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Paper Abstract

An equiripple FIR linear-phase digital filters design approach is proposed based on a novel neural network optimization technique. Its goal is to minimize the weight square-error function in the frequency domain. The design solution is presented as a parallel algorithm to approximate the desired frequency response specification, and the weight coefficients are updated according to error function. Thus, the proposed approximation method can avoid the overshoot phenomenon which may happen near the pass-band and stop-band edge of the designed filter, and may make a fast calculation of the filter's coefficients possible. Several optimal design examples are given and the performance comparison between the proposed design approach with some conventional methods, and the results show that the proposed neural network method can easily achieve higher design accuracy.

Paper Details

Date Published: 24 October 2006
PDF: 6 pages
Proc. SPIE 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence, 63570U (24 October 2006); doi: 10.1117/12.716901
Show Author Affiliations
Xiaohua Wang, Changsha Univ. of Science and Technology (China)
Hunan Univ. (China)
Yigang He, Hunan Univ. (China)
Shaosheng Fan, Changsha Univ. of Science and Technology (China)
Hong Li, Changsha Univ. of Science and Technology (China)


Published in SPIE Proceedings Vol. 6357:
Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence
Jiancheng Fang; Zhongyu Wang, Editor(s)

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