Name
Title | ||
|---|---|---|
Robust stability of Markovian jump discrete-time neural networks with partly unknown transition probabilities and mixed mode-dependent delays |
Abstract | ||
|---|---|---|
This article discusses the robust stability problem for a class of uncertain Markovian jump discrete-time neural networks with partly unknown transition probabilities and mixed mode-dependent time delays. The transition probabilities of the mode jumps are considered to be partly unknown, which relax the traditional assumption in Markovian jump systems that all of them must be completely known a priori. The mixed time delays consist of both discrete and distributed delays that are dependent on the Markovian jump modes. By employing the Lyapunov functional and linear matrix inequality approach, some sufficient criteria are derived for the robust stability of the underlying systems. A numerical example is exploited to illustrate the developed theory. |
Year | DOI | Venue |
|---|---|---|
2013 | 10.1080/00207721.2011.600472 | Int. J. Systems Science |
Keywords | Field | DocType |
mixed time delay,mixed mode-dependent delay,markovian jump discrete-time neural,robust stability,mode jump,robust stability problem,uncertain markovian jump discrete-time,markovian jump mode,transition probability,mixed mode-dependent time delay,unknown transition probability,markovian jump system,lyapunov function,linear matrix inequality,mixing time,recurrent neural network,development theory,discrete time,neural network | Discrete time neural networks,Mathematical optimization,Control theory,A priori and a posteriori,Mode (statistics),Markovian jump,Mixed mode,Artificial neural network,Lyapunov functional,Linear matrix inequality,Mathematics | Journal |
Volume | Issue | ISSN |
44 | 2 | 0020-7721 |
Citations | PageRank | References |
6 | 0.50 | 22 |
Authors | ||
2 | ||