Combination of Signal Segmentation Approaches using Fuzzy Decision Making

Hamed Azami, Javier Escudero

Research output: Contribution to conferencePaperpeer-review

Abstract

Segmentation is an important stage in signal analysis, and its performance plays a significant role in the efficiency of the subsequent steps, such as extraction of descriptive features and classification. There are a large number of approaches to segment signals. The performance of each of them remarkably varies when the signal changes. In this present study, two novel algorithms, which use the probability and fuzzy concepts, are proposed to combine several well-known existing signal segmentation approaches. The simulation results confirm the efficiency of the proposed approaches using the synthetic and real electroencephalogram signals.
Original languageEnglish
Pages101-104
Number of pages4
Publication statusPublished - 26 Aug 2015
Event37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - MiCo, Milan, Italy
Duration: 26 Aug 201529 Aug 2015

Conference

Conference37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Country/TerritoryItaly
CityMilan
Period26/08/1529/08/15

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