By Topic

Real-time design of FIR filters by feedback neural networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Bhattacharya, D. ; Dept. of Electr. & Comput. Eng., Victoria Univ., BC, Canada ; Antoniou, A.

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.

Published in:

Signal Processing Letters, IEEE  (Volume:3 ,  Issue: 5 )