Journal
NEURAL PROCESSING LETTERS
Volume 35, Issue 3, Pages 245-255Publisher
SPRINGER
DOI: 10.1007/s11063-012-9215-3
Keywords
Synchronization; Neural networks; Parameter identification; Sliding mode control; Adaptive control
Categories
Funding
- National Natural Science Foundation of China [10671209, 11071254]
- Scientific Research Foundation for the Returned Overseas Chinese Scholars, State Education Ministry
Ask authors/readers for more resources
The synchronization problem is studied in this paper for non-identical chaotic neural networks with time delays and fully unknown parameters, where the mismatched parameters, activation functions and neural network architectures are taken into account. To overcome the difficulty that complete synchronization of non-identical chaotic neural networks cannot be achieved only by utilizing output feedback control, we design an adaptive sliding mode controller to realize the synchronization. Our synchronization criteria are easily verified and do not need to solve any linear matrix inequality. These results generalize a few previous known results and remove some restrictions on the parameters, activation functions and neural network architectures. This paper also presents an illustrative example and uses simulated results of this example to show the feasibility and effectiveness of the proposed scheme.
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