Global Stability of a General Class of Discrete-Time Recurrent Neural Networks
โ Scribed by Zhigang Zeng; De-Shuang Huang; Zengfu Wang
- Publisher
- Springer US
- Year
- 2005
- Tongue
- English
- Weight
- 720 KB
- Volume
- 22
- Category
- Article
- ISSN
- 1370-4621
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
This paper is concerned with analysis problem for the global exponential stability of a class of recurrent neural networks (RNNs) with mixed discrete and distributed delays. We first prove the existence and uniqueness of the equilibrium point under mild conditions, assuming neither differentiability
Absa'act--The extraction of symbolic knowledge from trained neural networks and the direct encoding of (partial) knowledge into networks prior to training are important issues. They allow the exchange of information between symbolic and connectionist knowledge representations. The focas of this pape
The paper presents theoretical results on the global exponential periodicity and global exponential stability of a class of recurrent neural networks with various general activation functions and time-varying delays. The general activation functions include monotone nondecreasing functions, globally