A synthetic neural integrated circuit
- 1 January 1989
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 12.6/1-12.6/4
- https://doi.org/10.1109/cicc.1989.56743
Abstract
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 ideals. 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 describedKeywords
This publication has 2 references indexed in Scilit:
- A neuromorphic approach to adaptive digital circuitryPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Simple 'neural' optimization networks: An A/D converter, signal decision circuit, and a linear programming circuitIEEE Transactions on Circuits and Systems, 1986