Title :
Design of 2-D FIR filters by feedback neural networks
Author :
Bhattacharya, D. ; Antoniou, A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Victoria Univ., BC, Canada
fDate :
30 Apr-3 May 1995
Abstract :
A Hopfield-type neural network is proposed for the design of 2-D FIR filters. Given the amplitude response, the all-analog network computes the filter coefficients in real time. The network is simulated with HSPICE and a few examples are included to show that this is an efficient way of solving the approximation problem and has high potential for implementation in analog VLSI
Keywords :
FIR filters; Hopfield neural nets; SPICE; network synthesis; two-dimensional digital filters; 2D FIR filters; HSPICE simulation; Hopfield-type neural networks; amplitude response; analog VLSI; approximation problem; design; feedback neural networks; Computational modeling; Cost function; Finite impulse response filter; Frequency; Hopfield neural networks; Linear programming; Neural networks; Neurofeedback; Neurons; Transfer functions;
Conference_Titel :
Circuits and Systems, 1995. ISCAS '95., 1995 IEEE International Symposium on
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2570-2
DOI :
10.1109/ISCAS.1995.520383
