Scheduled System Maintenance:
Some services will be unavailable Sunday, March 29th through Monday, March 30th. We apologize for the inconvenience.
By Topic

Classical conditioning with pulsed integrated neural networks: circuits and system

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
1 Author(s)
Lehmann, T. ; Edinburgh Univ., UK

In this paper, we investigate on-chip learning for pulsed, integrated neural networks. We discuss the implementational problems the technology imposes on learning systems, and we find that a biologically inspired approach using simple circuit structures is most likely to bring success. We develop a suitable learning algorithm-a continuous-time version of a temporal differential Hebbian learning algorithm for pulsed neural systems with nonlinear synapses-as well as circuits for the electronic implementation. Measurements from an experimental CMOS chip are presented. Finally, we use our test chip to solve simple classical conditioning tasks, thus verifying the design methodologies put forward in the paper

Published in:

Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on  (Volume:45 ,  Issue: 6 )