Fast Identification Algorithm of Time-varying Modal Parameter Based on Two-layer Linear Neural Network Learning | Zendy

Kai Yang | Zendy; Kaiping Yu | Zendy

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Fast Identification Algorithm of Time-varying Modal Parameter Based on Two-layer Linear Neural Network Learning

Author(s) -

Kai Yang,

Kaiping Yu

Publication year - 2011

Publication title -

international journal of engineering and manufacturing

Language(s) - English

Resource type - Journals

eISSN - 2306-5982

pISSN - 2305-3631

DOI - 10.5815/ijem.2011.06.07

Subject(s) - subspace topology , artificial neural network , algorithm , modal , convergence (economics) , computer science , key (lock) , tracking (education) , identification (biology) , set (abstract data type) , layer (electronics) , artificial intelligence , psychology , pedagogy , chemistry , computer security , organic chemistry , economics , programming language , economic growth , botany , polymer chemistry , biology

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 new version of NIC(Novel Information Criterion) using two-layer linear neural network learning for subspace tracking. Comparing with the original algorithm, there is no need to set a key control parameter in advance. Simulation experiments show that new algorithm has a faster convergence in the initial period.

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