DocumentCode
2776779
Title
Dynamic behaviors of hybrid Lotka-Volterra recurrent neural networks with memristor characteristics
Author
Wu, Ailong ; Zeng, Zhigang
Author_Institution
Dept. of Control Sci. & Eng., Huazhong Univ. of Sci. & Technol., Wuhan, China
fYear
2012
fDate
10-15 June 2012
Firstpage
1
Lastpage
8
Abstract
In this paper, a general class of hybrid Lotka-Volterra recurrent neural networks with memristor characteristics is formulated and studied. Some sufficient conditions on nondivergence, global attractivity and complete stability of the network are obtained, respectively. These results can be applied to the memristive dynamic memories. The analysis in the paper employs results from the theory of differential equations with discontinuous right-hand side as introduced by Filippov. These theoretical analysis can characterize the fundamental electrical properties of memristor devices and provide convenience for applications. A numerical example is given to illustrate the theoretical findings via computer simulations.
Keywords
differential equations; memristors; recurrent neural nets; computer simulations; differential equations; discontinuous right-hand side; dynamic behaviors; electrical properties; hybrid Lotka-Volterra recurrent neural networks; memristive dynamic memories; memristor characteristics; memristor devices; network complete stability; network global attractivity; network nondivergence; Fires; Sensor arrays; Switches;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks (IJCNN), The 2012 International Joint Conference on
Conference_Location
Brisbane, QLD
ISSN
2161-4393
Print_ISBN
978-1-4673-1488-6
Electronic_ISBN
2161-4393
Type
conf
DOI
10.1109/IJCNN.2012.6252746
Filename
6252746
Link To Document