シャ　キンカ   Jinhua She   佘　錦華    所属   工学部 機械工学科    職種   教授
言語種別	英語
発行・発表の年月	2014/01
形態種別	学術論文
査読	査読あり
標題	Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks
執筆形態	共著
掲載誌名	Neural Networks
出版社・発行元	Elsevier
巻・号・頁	50(1),pp.98-109
担当範囲	All
著者・共著者	Ancai Zhang, Jianlong Qiu, and Jinhua She
概要	This paper concerns the existence and exponential stability of periodic solution for the high-order discrete-time bidirectional associative memory (BAM) neural networks with time-varying delays. First, we present the criteria for the existence of periodic solution based on the continuation theorem of coincidence degree theory and the Young's inequality, and then we give the criteria for the global exponential stability of periodic solution by using a non-Lyapunov method. After that, we give a numerical example that demonstrates the effectiveness of the theoretical results. The criteria presented in this paper are easy to verify. In addition, the proposed analysis method is easy to extend to other high-order neural networks.
DOI	DOI: 110.1016/j.neunet.2013.11.005