Fast Time-varying modal parameter identification algorithm based on two-layer linear neural network learning for subspace tracking

Fast Time-varying modal parameter identification algorithm based on two-layer linear neural network learning for subspace tracking

Автор: Kai Yang, Kaiping Yu

Журнал: International Journal of Information Engineering and Electronic Business(IJIEEB) @ijieeb

Статья в выпуске: 1 vol.3, 2011 года.

Бесплатный доступ

The key of fast identification algorithm of time-varying modal parameter based on subspace tracking is to find efficient and fast subspace-tracking algorithm. This paper presents a modified version of NIC(Novel Information Criterion) adopted in two-layer linear neural network learning for subspace tracking, which is applied in time-varying modal parameter identification algorithm based on subspace tracking and get a new time-varying modal parameter identification algorithm. Comparing with the original subspace-tracking algorithm, there is no need to set a key control parameter in advance. Simulation experiments show that new time-varying modal parameter identification algorithm has a faster convergence in the initial period and a real experiment under laboratory conditions confirms further its validity of the time-varying modal identification algorithm presented in this paper.

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Subspace tracking, time-varying modal parameter, identification algorithm, neural network learning

Короткий адрес: https://sciup.org/15013061

IDR: 15013061

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