DocumentCode
908772
Title
An adaptive neural processing node
Author
Donald, James ; Akers, Lex
Author_Institution
Center for Solid State Electron. Res., Arizona State Univ., Tempe, AZ, USA
Volume
4
Issue
3
fYear
1993
fDate
5/1/1993 12:00:00 AM
Firstpage
413
Lastpage
426
Abstract
The design and test results for two analog adaptive VLSI processing chips are described. These chips use pulse coded signals for communication between processing nodes and analog weights for information storage. The weight modification rule, implemented on chip, uses concepts developed by E. Oja (1982) and later extended by T. Leen et al. (1989) and T. Sanger (1989). Experimental results demonstrate that the network produces linearly separable outputs that correspond to dominant features of the inputs. Such representations allow for efficient additional neural processing. Part of the adaptation rule also includes a small number of fixed inputs and a variable lateral inhibition mechanism. Experimental results from the first chip show the operation of function blocks that make a single processing node. These function blocks include forward transfer function, weight modification, and inhibition. Experimental results from the second chip show the ability of an array of processing elements to extract important features from the input data
Keywords
VLSI; analogue processing circuits; neural chips; adaptation rule; adaptive VLSI processing chips; adaptive neural processing node; analog weights; analogue processing circuits; fixed inputs; forward transfer function; information storage; linearly separable outputs; pulse coded signals; variable lateral inhibition mechanism; weight modification; Adaptive control; Control systems; Delay lines; Feature extraction; Neural networks; Neurons; Signal processing; Testing; Transfer functions; Very large scale integration;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.217183
Filename
217183
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