A study of dynamic behavior of a recurrent neural network for control

Andrew Kim*, Chi haur Wu

*Corresponding author for this work

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

1 Scopus citations

Abstract

The dynamic behavior of a two-neuron recurrent network formulated from biological observations is studied. Different parameters that will affect the dynamic behavior of the network include decaying constant, synaptic weight, initial state of neuron, input to the system, and the activation function. The issues of stability, equilibrium state, and convergence time are explored. The convergence time is affected by the choice of decaying constant. In addition, the discontinuous activation function presents several favorable features over the continuous sigmoid function from the control point of view. Because of the discontinuity, equilibrium state can be separated into active region and inactive region. The active region can be triggered through the excitatory input, if the initial state is in the inactive region. The state of the equilibrium point is 'directly modulated by the input, which implies a unique input-output relationship.

Original languageEnglish (US)
Title of host publicationProceedings of the IEEE Conference on Decision and Control
PublisherPubl by IEEE
Pages150-155
Number of pages6
ISBN (Print)0780304500
StatePublished - Jan 1 1992
EventProceedings of the 30th IEEE Conference on Decision and Control Part 1 (of 3) - Brighton, Engl
Duration: Dec 11 1991Dec 13 1991

Other

OtherProceedings of the 30th IEEE Conference on Decision and Control Part 1 (of 3)
CityBrighton, Engl
Period12/11/9112/13/91

ASJC Scopus subject areas

  • Chemical Health and Safety
  • Control and Systems Engineering
  • Safety, Risk, Reliability and Quality

Fingerprint Dive into the research topics of 'A study of dynamic behavior of a recurrent neural network for control'. Together they form a unique fingerprint.

Cite this