One-dimensional signal classification by multiscale wavelet representation

Hamed Sari-Sarraf; Dragana P. Brzakovic

doi:10.1117/12.139935

20 August 1992 One-dimensional signal classification by multiscale wavelet representation

Hamed Sari-Sarraf, Dragana P. Brzakovic

Proceedings Volume 1706, Adaptive and Learning Systems; (1992) https://doi.org/10.1117/12.139935
Event: Aerospace Sensing, 1992, Orlando, FL, United States

Abstract

This paper describes a modular method for classification of 1-D signals which utilizes the shift-invariant MultiScale WAvelet Representation (MSWAR). The classification employs three modules. Representation module that uses the generalization of the multiresolution wavelet representation. Measurement module that uses local and global measures to establish measures of similarity between the reference and observed signals. And finally, classification module that employs a set of decision rules. These rules are derived based on theoretical and experimental considerations, and under specified conditions, guarantee the correct classification of observed signals with five types of deformities.

Citation Download Citation

Hamed Sari-Sarraf and Dragana P. Brzakovic "One-dimensional signal classification by multiscale wavelet representation", Proc. SPIE 1706, Adaptive and Learning Systems, (20 August 1992); https://doi.org/10.1117/12.139935

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