Title
Sampled-Data State Estimation of Neutral Type Neural Networks with Mixed Time-Varying Delays
Abstract
In this paper, we consider the problem of sampled-data control for neutral type neural networks with mixed time-varying delay components. A proper Lyapunov–Krasovskii functional is constructed by dividing the discrete and neutral delay intervals with triple and quadruplex integral terms. By employing the input delay approach, the sampling period is converted into a bounded time-vary delay in the estimation error dynamic. By employing Lyapunov-functional approach and utilizing LMI technique, sufficient conditions have been derived to guarantee that the estimation error dynamics is asymptotically stable. A numerical example is provided to illustrate the usefulness and effectiveness of the obtained results.
Year
DOI
Venue
2019
10.1007/s11063-018-9946-x
Neural Processing Letters
Keywords
Field
DocType
Interval time-varying delay,Linear matrix inequality,Lyapunov method,Neutral delay,Neural networks,Sampled-data control
Monad (category theory),Division (mathematics),Pattern recognition,Control theory,Sampling (signal processing),Artificial intelligence,Artificial neural network,Linear matrix inequality,Mathematics,Stability theory,Bounded function
Journal
Volume
Issue
ISSN
50
1
1573-773X
Citations 
PageRank 
References 
1
0.35
32
Authors
3
Name
Order
Citations
PageRank
M. Syed Ali151839.49
N. Gunasekaran231.72
Young Hoon Joo373876.87