DocumentCode
859398
Title
Real-time design of FIR filters by feedback neural networks
Author
Bhattacharya, D. ; Antoniou, A.
Author_Institution
Dept. of Electr. & Comput. Eng., Victoria Univ., BC, Canada
Volume
3
Issue
5
fYear
1996
fDate
5/1/1996 12:00:00 AM
Firstpage
158
Lastpage
161
Abstract
A Hopfield (1986) type neural network for the design of 1-D FIR filters is proposed. Given the frequency or amplitude response, the all-analog network computes the filter coefficients in real time. The network is simulated with HSPICE and examples are included to show that this is an efficient way of solving the approximation problem compared to the standard techniques for FIR filter design.
Keywords
FIR filters; Hopfield neural nets; SPICE; analogue processing circuits; approximation theory; circuit analysis computing; frequency response; low-pass filters; 1D FIR filters; FIR filter design; HSPICE; Hopfield type neural network; all-analog network; amplitude response; approximation problem solution; feedback neural networks; filter coefficients; frequency response; network simulation; real-time design; Computational modeling; Computer networks; Finite impulse response filter; Frequency response; Hopfield neural networks; Linear programming; Neural networks; Neurofeedback; Neurons;
fLanguage
English
Journal_Title
Signal Processing Letters, IEEE
Publisher
ieee
ISSN
1070-9908
Type
jour
DOI
10.1109/97.491661
Filename
491661
Link To Document