A DELAY-DEPENDENT APPROACH TO ROBUST STABILITY FOR UNCERTAIN HYBRID BIDIRECTIONAL ASSOCIATIVE MEMORY NEURAL NETWORKS WITH TIME-VARYING DELAYS

Authors

Chien-Yu Lu, Department of Industrial Education and Technology, National Changhua University of Education, Changhua, Taiwan 500, R.O.C
Koan-Yuh Chang, Department of Electronic Engineering, Chienkuo Technology University, Changhua 500, Taiwan, R.O.C
Hsun-Heng Tsai, Department of Biomechatronics Engineering, National Pingtung University of Science & Technology, Pingtung, Taiwan 912, R.O.C.
Wen-Jer Chang, Department of Marine Engineering, National Taiwan Ocean University, Keelung 202, Taiwan, R.O.CFollow

Abstract

This paper performs a global robust stability analysis of a particular class of hybrid bidirectional associative memory time-varying delayed neural network with norm-bounded timevarying parameter uncertainties. The activation functions are assumed to be globally Lipschitz continuous. Globally delay-dependent robust stability criteria are derived in the form of linear matrix inequalities by introducing relaxation matrices which, when chosen properly, produce a less conservative result. Two numerical examples are given to illustrate the significant improvement obtained in the conservativeness of the delay bound.

Recommended Citation

Lu, Chien-Yu; Chang, Koan-Yuh; Tsai, Hsun-Heng; and Chang, Wen-Jer (2010) "A DELAY-DEPENDENT APPROACH TO ROBUST STABILITY FOR UNCERTAIN HYBRID BIDIRECTIONAL ASSOCIATIVE MEMORY NEURAL NETWORKS WITH TIME-VARYING DELAYS," Journal of Marine Science and Technology: Vol. 18: Iss. 2, Article 2.
DOI: 10.51400/2709-6998.2315
Available at: https://jmstt.ntou.edu.tw/journal/vol18/iss2/2