Title :
Global robust stability of interval delayed neural networks
Author_Institution :
Dept. of Electr.-Electron. Eng., Atilim Univ., Ankara
fDate :
6/1/2009 12:00:00 AM
Abstract :
In recent years, the problem of global robust stability of Hopfield-type interval delayed neural networks has received considerable attention. A number of criteria for the global robust stability of such networks have been reported in the literature. On the basis of the idea of dividing (in respect of both the connection weight matrix A and the delayed connection weight matrix B) the given interval into two intervals, four new criteria for the global robust stability of such networks are established. The criteria are in the form of linear matrix inequality and, hence, computationally tractable. The criteria yield a less conservative condition compared with many recently reported criteria, as is demonstrated with an example.
Keywords :
Hopfield neural nets; delays; linear matrix inequalities; stability; Hopfield-type interval delayed neural networks; connection weight matrix; delayed connection weight matrix; global robust stability; linear matrix inequality;
Journal_Title :
Control Theory & Applications, IET
DOI :
10.1049/iet-cta.2008.0296