Neural network design approach for equiripple FIR digital filters

Xiaohua Wang; Yigang He; Shaosheng Fan; Hong Li

doi:10.1117/12.716901

24 October 2006 Neural network design approach for equiripple FIR digital filters

Xiaohua Wang, Yigang He, Shaosheng Fan, Hong Li

Proceedings Volume 6357, Sixth International Symposium on Instrumentation and Control Technology: Signal Analysis, Measurement Theory, Photo-Electronic Technology, and Artificial Intelligence; 63570U (2006) https://doi.org/10.1117/12.716901
Event: Sixth International Symposium on Instrumentation and Control Technology, 2006, Beijing, China

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.

Citation Download Citation

Xiaohua Wang, Yigang He, Shaosheng Fan, and Hong Li "Neural network design approach for equiripple FIR digital filters", 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); https://doi.org/10.1117/12.716901

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