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

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Listed:
  • Juan Chen
  • Zhenkun Huang
  • Jinxiang Cai

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.

Suggested Citation

  • Juan Chen & Zhenkun Huang & Jinxiang Cai, 2015. "Global Exponential Stability of Learning‐Based Fuzzy Networks on Time Scales," Abstract and Applied Analysis, John Wiley & Sons, vol. 2015(1).
    • Handle: RePEc:wly:jnlaaa:v:2015:y:2015:i:1:n:283519
    DOI: 10.1155/2015/283519
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    References listed on IDEAS

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    1. Huang, Tingwen, 2007. "Exponential stability of delayed fuzzy cellular neural networks with diffusion," Chaos, Solitons & Fractals, Elsevier, vol. 31(3), pages 658-664.
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