Optimal regulation of stochastic cellular neural networks using differential minimax game
Document Type
Conference Proceeding
Publication Date
9-20-2010
Abstract
In this paper, we present an approach to optimally regulate stochastic cellular neural networks by using differential minimax game. In order to realize the design, we consider the vector of external inputs as a player and that of internal noises as an opposing player. The purpose of this study is to achieve the best rational stabilization in probability for stochastic cellular neural networks, and to attenuate noises to a predefined level with stability margins under an optimal control strategy. A numerical example is given to demonstrate the effectiveness of the proposed approach. © 2010 IEEE.
Identifier
77956570979 (Scopus)
ISBN
[9781424477715]
Publication Title
Midwest Symposium on Circuits and Systems
External Full Text Location
https://doi.org/10.1109/MWSCAS.2010.5548775
ISSN
15483746
First Page
1214
Last Page
1217
Recommended Citation
Liu, Ziqian; Torres, Raul E.; and Ansari, Nirwan, "Optimal regulation of stochastic cellular neural networks using differential minimax game" (2010). Faculty Publications. 6080.
https://digitalcommons.njit.edu/fac_pubs/6080
