A Study of the Leaky-Integrator Recurrent Neural Dynamics and Its Applications
Document Type
Article
Publication Date
2006
Publication Title
Dynamics of Continuous, Discrete and Implusive Systems, Ser. A, Math. Anal.
Abstract
We study the characteristics of the leaky-integrator recurrent neural network dynamics and its applications. Our results show that the set of solutions of the dynamical system is positive invariant and attractive for the continuous-time recurrent neural network model. For the discrete-time recurrent neural network model, the stability analysis has been provided. Examples are given to demonstrate how our approaches can be applied to compress the data and perform the global optimization techniques to the nonlinear regression models effectively. The method offers an ideal setting to carry out the recurrent neural network approach to different areas including engineering, business and statistics.
Repository Citation
Leong Kwan Li & Sally S. L. Shao. (2006). A Study of the Leaky-Integrator Recurrent Neural Dynamics and Its Applications. Dynamics of Continuous, Discrete and Implusive Systems, Ser. A, Math. Anal., 353-366.
Original Citation
Leong Kwan Li & Sally S. L. Shao. (2006). A Study of the Leaky-Integrator Recurrent Neural Dynamics and Its Applications. Dynamics of Continuous, Discrete and Implusive Systems, Ser. A, Math. Anal., 353-366.