A Fast Neural Network Simulator for State Transition Analysis

Atsushi KAMO  Hiroshi NINOMIYA  Teru YONEYAMA  Hideki ASAI  

Publication
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences   Vol.E82-A   No.9   pp.1796-1801
Publication Date: 1999/09/25
Online ISSN: 
DOI: 
Print ISSN: 0916-8508
Type of Manuscript: Special Section PAPER (Special Section on Nonlinear Theory and Its Applications)
Category: 
Keyword: 
stepwise constant method,  multivalued neural network,  ASSIST,  state transition analysis,  

Full Text: PDF>>
Buy this Article




Summary: 
This paper describes an efficient simulator for state transition analysis of multivalued continuous-time neural networks, where the multivalued transfer function of neuron is regarded as a stepwise constant one. Use of stepwise constant method enables to analyse the state transition of the network without solving explicitly the differential equations. This method also enables to select the optimal timestep in numerical integration. The proposed method is implemented on the simulator and applied to the general neural network analysis. Furthermore, this is compared with the conventional simulators. Finally, it is shown that our simulator is drastically faster and more practical than the conventional simulators.