One-dimensional signal classification by multiscale wavelet representation

Hamed Sari-Sarraf, Dragana Brzakovic

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


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.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherPubl by Int Soc for Optical Engineering
Number of pages11
ISBN (Print)0819408719
StatePublished - 1992
EventAdaptive and Learning Systems - Orlando, FL, USA
Duration: Apr 20 1992Apr 21 1992

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


ConferenceAdaptive and Learning Systems
CityOrlando, FL, USA


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