Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
409371 | Neurocomputing | 2007 | 5 Pages |
Abstract
This letter investigates convergence theorems of a DHNN with delay. We present one generalized updating rule for serial mode. The condition for convergence of a DHNN without delay can be relaxed from a symmetric matrix to a quasi-symmetric matrix. One application is presented to demonstrate the higher convergence speed of our algorithm.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Eric C.C. Tsang, S.S. Qiu, Daniel S. Yeung,