Abstract
This paper is concerned with analyzing mean square exponential stability of stochastic delayed neural networks subject to parametric uncertainties. The discretized Lyapunov functional technique is first utilized to construct a new Lyapunov functional in order to effectively deal with the time-varying delay. Then the free-weighting matrix technique and the convex combination method are used to establish a new delay-dependent mean square exponential stability criterion for uncertain stochastic delayed neural networks. The usefulness of the new theoretical findings is further demonstrated by numerical results.
| Original language | English |
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| Title of host publication | Proceedings of the 43rd IEEE International Symposium on Circuits and Systems (ISCAS 2010) : Nano-Bio Circuit Fabrics and Systems, Paris France, 30 May - 2 June 2010 |
| Publisher | IEEE Press |
| Pages | 2562-2565 |
| Number of pages | 4 |
| ISBN (Print) | 9781424453092 |
| Publication status | Published - 2010 |
| Event | IEEE International Symposium on Circuits and Systems - Duration: 20 May 2012 → … |
Conference
| Conference | IEEE International Symposium on Circuits and Systems |
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| Period | 20/05/12 → … |
Keywords
- neural networks (computer science)
- stochastic processes