IEICE TRANSACTIONS on Fundamentals
A Fast Neural Network Simulator for State Transition Analysis
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.
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- IEICE TRANSACTIONS on Fundamentals Vol.E82-A No.9 pp.1796-1801
- Publication Date
- 1999/09/25
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- Special Section PAPER (Special Section on Nonlinear Theory and Its Applications)
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Atsushi KAMO, Hiroshi NINOMIYA, Teru YONEYAMA, Hideki ASAI, "A Fast Neural Network Simulator for State Transition Analysis" in IEICE TRANSACTIONS on Fundamentals,
vol. E82-A, no. 9, pp. 1796-1801, September 1999, doi: .
Abstract: 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.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e82-a_9_1796/_p
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@ARTICLE{e82-a_9_1796,
author={Atsushi KAMO, Hiroshi NINOMIYA, Teru YONEYAMA, Hideki ASAI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Fast Neural Network Simulator for State Transition Analysis},
year={1999},
volume={E82-A},
number={9},
pages={1796-1801},
abstract={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.},
keywords={},
doi={},
ISSN={},
month={September},}
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TY - JOUR
TI - A Fast Neural Network Simulator for State Transition Analysis
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 1796
EP - 1801
AU - Atsushi KAMO
AU - Hiroshi NINOMIYA
AU - Teru YONEYAMA
AU - Hideki ASAI
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E82-A
IS - 9
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - September 1999
AB - 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.
ER -
English
