ISSN:
1432-0770
Source:
Springer Online Journal Archives 1860-2000
Topics:
Biology
,
Computer Science
,
Physics
Notes:
Abstract Double-layer neural networks with mutually inhibiting interconnections are analyzed using a continuous-variable model of the neuron. The first layer consists of excitatory neurons while the second layer consists of inhibitory neurons. Both feedforward and feedback interconnections exist between the two layers. An autonomous system of nonlinear differential equations is introduced to describe the network dynamics, and the stability conditions for some classes of equilibria are investigated in detail. Several simulation results are also presented. It is shown that even those networks which are formed with rather powerless synapses are capable of carrying out input pattern sharpening, temporary information storage, and periodic signal generation.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF00337266
