Synthetic neural integrated circuit

L. A. Akers, M. Walker, R. Grondin, D. Ferry

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


Integrated circuits are approaching biological complexity in device count. Biological systems are fault tolerant, adaptive, and trainable, and the possibility exists for similar characteristics in ICs. The authors report a limited-interconnect, highly layered synthetic neural network that implements these ideas. These networks are specifically designed to scale to tens of thousands of processing elements on current production size dies. A compact analog cell, a training algorithm, and a limited-interconnect architecture which has demonstrated neuromorphic behavior are described.

Original languageEnglish (US)
Title of host publicationProceedings of the Custom Integrated Circuits Conference
Editors Anon
PublisherPubl by IEEE
StatePublished - May 1989
EventProceedings of the IEEE 1989 Custom Integrated Circuits Conference - San Diego, CA, SA
Duration: May 15 1989May 18 1989


OtherProceedings of the IEEE 1989 Custom Integrated Circuits Conference
CitySan Diego, CA, SA

ASJC Scopus subject areas

  • Electrical and Electronic Engineering


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