On the state space of the binary neural network.

Moshe Kam, Roger Cheng, Allon Guez

Research output: Contribution to journalConference articlepeer-review


The authors discuss the case of deterministic known codewords for which storage is required and show that bounds on the retrieval probabilities and convergence rates can be achieved. The main tool which they use is birth-and-death Markov chains, describing the Hamming distance of the network's state from the stored patterns. The results are applicable to both the asynchronous network and to the Boltzmann machines and can be utilized to compare codeword sets in terms of efficiency of their retrieval when the neural network is used as a content addressable memory.

Original languageEnglish (US)
Pages (from-to)2276-2281
Number of pages6
JournalProceedings of the American Control Conference
Volume88 pt 1-3
StatePublished - 1988
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Electrical and Electronic Engineering


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