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Nonlinear signal classification using geometric statistical features in state space

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1 Author(s)
Yang, S. ; Dept. of Comput. Sci. & Eng., Fudan Univ., Shanghai, China

A new methodology in the framework of high-dimensional shape analysis in state space is proposed for nonlinear signal classification. The zero-crossing rate on a Poincare surface of a section is used as a feature. Experiments regarding oceanic signal classification show that the proposed methodology can provide some information not contained in spectra.

Published in:

Electronics Letters  (Volume:40 ,  Issue: 12 )

Date of Publication:

10 June 2004

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