Global Uniform Asymptotic Fixed Deviation Stability and Stability for Delayed Fractional-order Memristive Neural Networks with Generic Memductance.
basic_science · Level V
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- Record sourced from PubMed, PMID 29190495.
- Also identified by DOI 10.1016/j.neunet.2017.11.004.
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Abstract
In this paper, we study global uniform asymptotic fixed deviation stability and stability for a wide class of memristive neural networks with time-varying delays. Firstly, a new mathematical expression of the generic memductance (memristance) is proposed according to the feature of the memristor and the general current-voltage characteristic and a new class of neural networks is designed. Next, a new concept of stability (fixed deviation stability) is proposed in order to describe veritably the stability characteristics of the discontinuous system and the sufficient conditions are given to guarantee the global uniform asymptotic fixed deviation stability and stability of the new system. Finally, two numerical examples are provided to show the applicability and effectiveness of our main results.
Medical subject headings
- Machine Learning
- Neural Networks, Computer