Parallel architectures for artificial neural nets.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

30 Scopus citations


The key aspects of the modeling, algorithm, and architecture for artificial neural nets (ANNs) is reviewed. A programmable systolic array meant for a variety of connectivity patterns for ANNs is proposed. Considered in the design are both the search and learning phases of a class of ANNs. A system-theoretic approach is adopted to elucidate modeling issues for ANNs. On this basis the issues of expressibility and discrimination, fault tolerance and generalization, size of hidden units/layers, interconnectivity patterns, and circuit model for analog ANN implementations are addressed.

Original languageEnglish (US)
Title of host publicationProc Int Conf on Systolic Arrays
PublisherPubl by IEEE
Number of pages12
ISBN (Print)0818688602
StatePublished - 1988

Publication series

NameProc Int Conf on Systolic Arrays

All Science Journal Classification (ASJC) codes

  • General Engineering


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