Global Exponential Stability of Learning‐Based Fuzzy Networks on Time Scales

Juan Chen, Zhenkun Huang and Jinxiang Cai

Abstract and Applied Analysis, 2015, vol. 2015, issue 1

Abstract: We investigate a class of fuzzy neural networks with Hebbian‐type unsupervised learning on time scales. By using Lyapunov functional method, some new sufficient conditions are derived to ensure learning dynamics and exponential stability of fuzzy networks on time scales. Our results are general and can include continuous‐time learning‐based fuzzy networks and corresponding discrete‐time analogues. Moreover, our results reveal some new learning behavior of fuzzy synapses on time scales which are seldom discussed in the literature.

Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
https://doi.org/10.1155/2015/283519

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:wly:jnlaaa:v:2015:y:2015:i:1:n:283519

Access Statistics for this article

More articles in Abstract and Applied Analysis from John Wiley & Sons
Bibliographic data for series maintained by Wiley Content Delivery ().