✦ LIBER ✦

Information storage in high-order neural networks with unequal neural activity

✍ Scribed by Heng-Ming Tai; Tai-Lang Jong

Publisher: Elsevier Science
Year: 1990
Tongue: English
Weight: 736 KB
Volume: 327
Category: Article
ISSN: 0016-0032
DOI: 10.1016/0016-0032(90)90061-m

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✦ Synopsis

Neural networks with high-order interactions only have been shown to be sujicient to provide satisfactory attractivity to the storedpatterns and error corrections. Such interactions increase the storage capacity of the networks and allow one to solve a class of problems which are intractable with standard networks. In this paper we analyse the capacity of these higher-order networks by the statistical method and show why the probability of the states of neurons being active and passive can always be chosen equal, i.e. with a probability ~$0.5 each.

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