DocumentCode
288566
Title
Random parameter variation in analog VLSI neural networks for linear image filtering
Author
Shi, B.E. ; Roska, T. ; Chua, L.O.
Author_Institution
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA
Volume
3
fYear
1994
fDate
27 Jun-2 Jul 1994
Firstpage
1917
Abstract
This paper introduces an analytic method to determine the sensitivity to random parameter variations of analog VLSI neural network architectures for linear image filtering. The authors compare the robustness of several different circuit architectures for low pass filtering. This method can also determine which components within a particular architecture should specified the most precisely
Keywords
VLSI; analogue processing circuits; filtering theory; image processing; low-pass filters; neural chips; neural net architecture; analog VLSI neural networks; circuit architectures; linear image filtering; low pass filtering; random parameter variation; robustness; sensitivity; Cellular neural networks; Circuits; Computer architecture; Filtering; Intelligent networks; Low pass filters; Neural networks; Nonlinear filters; Robustness; Very large scale integration;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location
Orlando, FL
Print_ISBN
0-7803-1901-X
Type
conf
DOI
10.1109/ICNN.1994.374453
Filename
374453
Link To Document