Electronic Journal of Differential Equations,
Vol. 2006(2006), No. 32, pp. 1-21.

Title: Existence and exponential stability of
       periodic solution for continuous-time and discrete-time
       generalized bidirectional neural networks
       
Author: Yongkun Li (Yunnan Univ., China)

Abstract: 
 We study the existence and global exponential stability of positive
 periodic solutions for a class of continuous-time generalized
 bidirectional neural networks with variable coefficients and
 delays. Discrete-time analogues of the continuous-time networks
 are formulated and the existence and global exponential
 stability of positive periodic solutions are studied
 using the continuation theorem of coincidence degree theory
 and Lyapunov functionals.
 It is shown that the existence and global exponential
 stability of positive periodic solutions of the continuous-time
 networks are preserved by the discrete-time analogues under some
 restriction on the discretization step-size.
 An example is given to illustrate the results obtained. 
 
Submitted February 16, 2006. Published March 16, 2006.
Math Subject Classifications: 34K13, 34K25.
Key Words: Bidirectional neural  networks;  global exponential stability;
           periodic solution; Fredholm mapping; Lyapunov functionals;
           discrete-time analogues.