Title :
VLSI implementation of cellular neural networks
Author :
Yang, L. ; Chua, L.O. ; Krieg, K.R.
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., California Univ., Berkeley, CA, USA
Abstract :
A cellular neural network (CNN) which is an example of very-large-scale analog processing or collective analog computation is presented. The CNN architecture combines some features of fully connected analog neural networks with the nearest-neighbor interactions found in cellular automata. VLSI implementation of these circuits is discussed. Though the circuits described have been fabricated for noise removal and connected segment extraction, most of the features of the VLSI circuits are shared by VLSI implementations of other processing functions
Keywords :
VLSI; analogue computer circuits; computer architecture; neural nets; pattern recognition; VLSI implementation; cellular neural networks; collective analog computation; connected segment extraction; fully connected analog neural networks; nearest-neighbor interactions; noise removal; very-large-scale analog processing; Analog computers; Cellular neural networks; Circuit noise; Computer architecture; Fabrication; Feedback circuits; Force feedback; Large-scale systems; Neural networks; Very large scale integration;
Conference_Titel :
Circuits and Systems, 1990., IEEE International Symposium on
Conference_Location :
New Orleans, LA
DOI :
10.1109/ISCAS.1990.112500