DocumentCode :
3044666
Title :
Analogous memory utilization-a necessary characteristic for large, adaptive neural net
Author :
Fortune, James A.
Author_Institution :
Oakland Univ., Rochester, MI, USA
fYear :
1989
fDate :
14-17 Nov 1989
Firstpage :
1268
Abstract :
When confronted with new knowledge structured in a familiar way humans often rely on analogy to make a one-to-one correspondence to the familiar structure. The author notes that efficient adaptive neural nets also have that characteristic. In fact, the absence of analogous memory utilization from a system will be obvious because the resulting uncontrolled redundancy will quickly fill new memory with an exponential explosion of redundant information. The resulting decrease in performance is rapid and dramatic. A discussion is presented of why proper use of available memory will produce analogous memory utilization automatically
Keywords :
knowledge engineering; memory architecture; neural nets; adaptive neural net; analogous memory utilization; redundancy; Artificial intelligence; Biological neural networks; Entropy; Explosions; Hardware; Humans; Natural languages; Neural networks; Robot motion; Speech recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Man and Cybernetics, 1989. Conference Proceedings., IEEE International Conference on
Conference_Location :
Cambridge, MA
Type :
conf
DOI :
10.1109/ICSMC.1989.71507
Filename :
71507
Link To Document :
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