Research on Stability Analysis for Delayed Neural Networks

• Main Authors: Yen-Feng Lin, 林晏烽
• Other Authors: Chang-Hua Lien
• Format: Others
• Language: zh-TW
• Published: 2009
• Online Access: http://ndltd.ncl.edu.tw/handle/04475318518141493084

碩士 === 國立高雄海洋科技大學 === 輪機工程研究所 === 97 === In this dissertation, we will investigate the global exponential stability for uncertain delayed neural networks (DNNs) of neutral type and Cohen-Grossberg neural networks (CGNNs) with time varying delays. Delay-dependent and delay-independent stability criteria are proposed to guarantee the robust stability and uniqueness of equilibrium point via linear matrix inequality (LMI) and Razumikhin-like approaches. In Chapter 3, we will investigate the delayed neural networks of neutral type with structured perturbations and norm-bounded unstructured perturbations. In Chapter 4, we will investigate the delayed Cohen-Grossberg neural networks with structured perturbations, norm-bounded unstructured perturbations, and interval system perturbations. Finally, some numerical examples are illustrated to show the effectiveness of our results.