Journal of Applied Mathematics

Almost Periodic Solutions for Neutral-Type BAM Neural Networks with Delays on Time Scales

Yongkun Li and Li Yang

Full-text: Open access

Abstract

Using the existence of the exponential dichotomy of linear dynamic equations on time scales, a fixed point theorem and the theory of calculus on time scales, we obtain some sufficient conditions for the existence and exponential stability of almost periodic solutions for a class of neutral-type BAM neural networks with delays on time scales. Finally, a numerical example illustrates the feasibility of our results and also shows that the continuous-time neural network and its discrete-time analogue have the same dynamical behaviors. The results of this paper are completely new even if the time scale 𝕋= or and complementary to the previously known results.

Article information

Source
J. Appl. Math., Volume 2013 (2013), Article ID 942309, 13 pages.

Dates
First available in Project Euclid: 14 March 2014

Permanent link to this document
https://projecteuclid.org/euclid.jam/1394808048

Digital Object Identifier
doi:10.1155/2013/942309

Mathematical Reviews number (MathSciNet)
MR3074331

Zentralblatt MATH identifier
1271.92005

Citation

Li, Yongkun; Yang, Li. Almost Periodic Solutions for Neutral-Type BAM Neural Networks with Delays on Time Scales. J. Appl. Math. 2013 (2013), Article ID 942309, 13 pages. doi:10.1155/2013/942309. https://projecteuclid.org/euclid.jam/1394808048


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