Deriving Sufficient Conditions for Global Asymptotic Stability of Delayed Neural Networks Via Nonsmooth Analysis-II  

Oleh:

Qi, Houduo ; Qi, Liqun ; Yang, Xiaoqi

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 16 no. 6 (Nov. 2005), page 1701-1706.
Topik: neural network; asymptotic stability; delayed; neural networks; non smooth analysis

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Following our recent approach of nonsmooth analysis, we report a new set of sufficient conditions and its implications for the global asymptotic stability of delayed cellular neural networks (DCNN). The new conditions not only unify a string of previous stability results, but also yield strict improvement over them by allowing the symmetric part of the feedback matrix positive definite, hence enlarging the application domain of DCNNs. Advantages of the new results over existing ones are illustrated with examples. We also compare our results with those related results obtained via LMI approach.

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