Journal
IEEE TRANSACTIONS ON NEURAL NETWORKS
Volume 21, Issue 1, Pages 91-106Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNN.2009.2034742
Keywords
Delay-dependent stability; recurrent neural networks (RNNs); time-varying delay; weighting delay
Categories
Funding
- National Natural Science Foundation of China [50977008, 60774048]
- Program for Cheung Kong Scholars
- National Basic Research Program of China [2009CB320601]
- Doctoral Program of Higher Education of China [200801451096]
- China Postdoctoral Science Foundation [20080431150]
Ask authors/readers for more resources
In this paper, a weighting-delay-based method is developed for the study of the stability problem of a class of recurrent neural networks (RNNs) with time-varying delay. Different from previous results, the delay interval [0, d(t)] is divided into some variable subintervals by employing weighting delays. Thus, new delay-dependent stability criteria for RNNs with time-varying delay are derived by applying this weighting-delay method, which are less conservative than previous results. The proposed stability criteria depend on the positions of weighting delays in the interval [0, d(t)], which can be denoted by the weighting-delay parameters. Different weighting-delay parameters lead to different stability margins for a given system. Thus, a solution based on optimization methods is further given to calculate the optimal weighting-delay parameters. Several examples are provided to verify the effectiveness of the proposed criteria.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available