title: Existence and global exponential stability of periodic solution for high-order discrete-time BAM neural networks.
abstract: 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.
authors.affiliation: School of Automobile Engineering, Linyi University, Linyi, Shandong 276005, China. Electronic address: zhangancai123@hotmail.com.
authors.forename: Ancai
authors.initials: A
authors.lastname: Zhang
authors.affiliation: School of Science, Linyi University, Linyi, Shandong 276005, China. Electronic address: qjllinyi@aliyun.com.
authors.forename: Jianlong
authors.initials: J
authors.lastname: Qiu
authors.affiliation: School of Computer Science, Tokyo University of Technology, Hachioji, Tokyo 192-0982, Japan. Electronic address: she@stf.teu.ac.jp.
authors.forename: Jinhua
authors.initials: J
authors.lastname: She
mesh_terms: D000465:Algorithms; D001245:Association Learning / Q000502:physiology; D003198:Computer Simulation; D006801:Humans; D008568:Memory / Q000502:physiology*; D016571:Neural Networks, Computer; D013997:Time Factors
keywords: Bidirectional associative memory (BAM); Discrete-time; Exponential stability; High-order neural networks; Young’s inequality