Title :
Real-time synthesis of FIR filters in frequency domain by feedback neural nets
Author :
Bhattacharya, Dipankar ; Antoniou, Andreas
Author_Institution :
Dept. of Electr. & Comput. Eng., Victoria Univ., BC, Canada
Abstract :
A Hopfield-type neural network is proposed for the synthesis of FIR filters. Given the amplitude response in the frequency domain the all-analog network computes the filter coefficients in real time. The network is simulated with HSPICE and two examples are included to show that this is an efficient way of computing filter coefficients compared to the standard techniques for FIR filter design
Keywords :
FIR filters; Hopfield neural nets; SPICE; active filters; analogue processing circuits; circuit CAD; frequency-domain synthesis; FIR filters; HSPICE; Hopfield-type neural network; all-analog network; amplitude response; feedback neural nets; filter coefficients; filter design; frequency domain; real-time synthesis; Computational modeling; Computer networks; Cost function; Feedback; Finite impulse response filter; Frequency domain analysis; Hopfield neural networks; Intelligent networks; Linear programming; Network synthesis; Neural networks; Neurofeedback; Neurons;
Conference_Titel :
Circuits and Systems, 1994., Proceedings of the 37th Midwest Symposium on
Conference_Location :
Lafayette, LA
Print_ISBN :
0-7803-2428-5
DOI :
10.1109/MWSCAS.1994.518996
