DocumentCode
1752947
Title
A Novel Neural Networks-Based Approach for Designing FIR Filters
Author
Wang, Xiaohua ; Meng, Xianzhi ; He, Yigang
Author_Institution
Coll. of Electr. & Inf. Eng., Changsha Univ. of Sci. & Technol.
Volume
1
fYear
0
fDate
0-0 0
Firstpage
4029
Lastpage
4032
Abstract
A novel linear-phase finite-impulse response (FIR) digital filters design approach based on neural networks optimization technique was proposed in this paper. The main idea is to minimize the weighted square-error function in the frequency-domain. The convergence theorem of the neural networks algorithm was presented and proved to illustrate the proposed algorithm stable, and the implementation of the approach was also described together with some design guidelines. This method can control the overshoot phenomenon that may happen near the pass-band and stop-band edge of the designed filter. Some optimal design examples were given to illustrate the effectiveness of the proposed optimal design method
Keywords
FIR filters; linear phase filters; neural nets; convergence theorem; frequency domain; linear-phase finite-impulse response digital filters; neural network optimization; weighted square-error function; Algorithm design and analysis; Convergence; Design engineering; Digital filters; Educational institutions; Finite impulse response filter; Frequency; Least squares methods; Neural networks; Sampling methods; FIR filter; Neural networks; convergence theorem; optimal design;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
Conference_Location
Dalian
Print_ISBN
1-4244-0332-4
Type
conf
DOI
10.1109/WCICA.2006.1713130
Filename
1713130
Link To Document