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A model of neural circuits for programmable VLSI implementation

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1 Author(s)
Salam, F.M.A. ; Dept. of Electr. Eng., Michigan State Univ., East Lansing, MI, USA

A new model for neural circuits is introduced which has qualitatively the same dynamic properties as gradient continuous-time feedback neural nets. This model (i) reduces the maximum number of connections to n(n+1)/2, (ii) does not suffer from the synaptic weight problem, i.e. the problem of implementing variable linear resistive elements in large scale, and (iii) is implementable via all MOS elements. Hence, it lends itself naturally to analog MOS VLSI implementation

Published in:

Circuits and Systems, 1989., IEEE International Symposium on

Date of Conference:

8-11 May 1989