DocumentCode
232048
Title
Almost periodicity in a harvesting Lotka-Volterra recurrent neural networks with mixed delays and impulses
Author
Yao Xiaojie ; Qin Fajin
Author_Institution
Dept. of Math. & Comput. Sci., Liuzhou Teachers Coll., Liuzhou, China
fYear
2014
fDate
28-30 July 2014
Firstpage
5107
Lastpage
5112
Abstract
By using the theory of exponential dichotomy and Banach fixed point theorem, this paper is concerned with the problem of the existence and uniqueness of positive almost periodic solution in a harvesting Lotka-Volterra recurrent neural networks with mixed delays and impulses. To a certain extent, our work in this paper extend and improve some result in recent years. Finally, an example is given to illustrate the feasibility and effectiveness of the main result.
Keywords
Volterra equations; delays; neural nets; Banach fixed point theorem; exponential dichotomy; harvesting Lotka-Volterra recurrent neural networks; mixed delays; mixed impulses; Computer science; Delays; Educational institutions; Electronic mail; Mathematics; Recurrent neural networks; Sufficient conditions; Impulses; Lotka-Volterra Recurrent Neural Networks; Mixed Delays; Positive Almost Periodic Solution;
fLanguage
English
Publisher
ieee
Conference_Titel
Control Conference (CCC), 2014 33rd Chinese
Conference_Location
Nanjing
Type
conf
DOI
10.1109/ChiCC.2014.6895809
Filename
6895809
Link To Document