Modeling and qualitative analysis of continuous-time neural networks under pure structural variations

✍ Scribed by Ljubomir T. Grujić; Anthony N. Michel

• Publisher: Elsevier Science
• Year: 1996
• Tongue: English
• Weight: 566 KB
• Volume: 40
• Category: Article
• ISSN: 0378-4754
• DOI: 10.1016/0378-4754(95)00004-6

✦ Synopsis

A qualitative analysis is developed for continuous-time neural networks subjected to random pure structural variations. Simple algebraic conditions are established for both structural exponential stability of x = 0 of the neural network and for estimates of its domain of attraction. Bounds on motions of the neural network in a forced regime are provided. They do not require any information about its actual structure, which can be completely unknown and may vary unpredictably.