Some New Results on System Identification With Dynamic Neural Networks  

Oleh:

Yu, Wen ; Li, Xiaoou

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: IEEE Transactions on Neural Networks vol. 12 no. 2 (2001), page 412-417.
Topik: NEURAL NETWORKS; results; system identification; dynaic neural networks

Ketersediaan

Perpustakaan Pusat (Semanggi) Nomor Panggil: II36.5 Non-tandon: 1 (dapat dipinjam: 0) Tandon: tidak ada

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Isi artikel

Non linear system online identification via dynamic neural networks is studied in this paper. The main contribution of the paper is that the passivity approach is applied to access several new stable properties of neuro identification. The conditions for passivity, stability, asymptotic stability, and input - to - state stability are established in certain senses. We conclude that the gradient descent algorithm for weight adjustment is stable in an L 8 sense and robust to any bounded uncertainties.

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