Combination of Signal Segmentation Approaches using Fuzzy Decision Making

Hamed Azami; Javier Escudero

Combination of Signal Segmentation Approaches using Fuzzy Decision Making

Research output: Contribution to conference › Paper › peer-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 language	English
Pages	101-104
Number of pages	4
Publication status	Published - 26 Aug 2015
Event	37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - MiCo, Milan, Italy Duration: 26 Aug 2015 → 29 Aug 2015

Conference

Conference	37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
Country/Territory	Italy
City	Milan
Period	26/08/15 → 29/08/15

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title = "Combination of Signal Segmentation Approaches using Fuzzy Decision Making",

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.",

author = "Hamed Azami and Javier Escudero",

note = "Date of Acceptance: 31/05/2015 ; 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society ; Conference date: 26-08-2015 Through 29-08-2015",

year = "2015",

month = aug,

day = "26",

language = "English",

pages = "101--104",

}

TY - CONF

T1 - Combination of Signal Segmentation Approaches using Fuzzy Decision Making

AU - Azami, Hamed

AU - Escudero, Javier

N1 - Date of Acceptance: 31/05/2015

PY - 2015/8/26

Y1 - 2015/8/26

N2 - 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.

AB - 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.

M3 - Paper

SP - 101

EP - 104

T2 - 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society

Y2 - 26 August 2015 through 29 August 2015

ER -

Combination of Signal Segmentation Approaches using Fuzzy Decision Making

Abstract

Conference

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