Delay-dependent stability for neural networks with time-varying delays via a novel partitioning method

NEUROCOMPUTING

卷:173

Article

Yang, Bin¹  Wang, Rui²  Dimirovski, Georgi M.^3,4 

[1] Dalian Univ Technol, Sch Control Sci & Engn, Dalian 116024, Peoples R China

[2] Dalian Univ Technol, Sch Aeronaut & Astronaut, State Key Lab Struct Anal Ind Equipment, Dalian 116024, Peoples R China

[3] Dogus Univ, Sch Engn, TR-34722 Istanbul, Turkey

[4] St Cyril & St Methodius Univ, Sch FEIT, MK-1000 Skopje, North Macedonia

关键词: Neural networks;    Time-varying delay;    Stability;    Lyapunov-Krasovskii functional;    Wirtinger integral inequality;   

DOI  :  10.1016/j.neucom.2015.08.058

来源: Elsevier

【 摘 要 】

In this brief, a novel partitioning method for the conditions on bounding the activation function in the stability analysis of neural networks systems with time-varying delays is presented. Certain further improved delay-dependent stability conditions, which are expressed in terms of linear matrix inequalities (LMIs), are derived by employing a suitable Lyapunov-Krasovskii functional (LKF) and utilizing the Wirtinger integral inequality. Two well-known examples are investigated in a comparison mode with results to show the effectiveness and improvements achieved by the new results proposed. (C) 2015 Elsevier B.V. All rights reserved.

【 授权许可】

Free