Affiliation:
1. School of Mathematical Science Heilongjiang University Harbin People's Republic of China
2. Heilongjiang Provincial Key Laboratory of the Theory and Computation of Complex Systems Heilongjiang University Harbin Heilongjiang People's Republic of China
3. School of Automation Beijing Institute of Technology Beijing People's Republic of China
Abstract
AbstractThis article investigates the exponential control issue of bidirectional associative memory neural network (BAMNN) with unbounded time‐varying delays. A bounded real lemma (BRL) is first established via a direct method, which is on the basis of the solutions of BAMNN. Second, based on the obtained BRL, the state feedback controller is designed to guarantee the global exponential stability of the resulting closed‐loop BAMNN with an performance index. Since no Lyapunov–Krasovskii functionals is constructed in the proposed method, the computation burden and complexity are reduced. Lastly, the effectiveness of the theoretical results is illustrated through two numerical examples.
Funder
National Natural Science Foundation of China
China Postdoctoral Science Foundation
Natural Science Foundation of Heilongjiang Province