New Classification Attributes for Signal Separation in Acoustic Emission Processing

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21340%2F10%3A00176063" target="_blank" >RIV/68407700:21340/10:00176063 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

New Classification Attributes for Signal Separation in Acoustic Emission Processing

Original language description

We deal with the classification of acoustic emission random signals by means of fuzzy clustering, model-based statistical clustering and support vector machines. The signals are compared by means of newly introduced attributes obtained directly from thesignals and from normed frequency spectra such as phi-divergence distance measure originated from information theory and statistics. We mention the well-known divergences (Kullback, Hellinger, Chi , Power) and we introduce several of its new modifications and extensions as generalized Hellinger divergences. These new families of divergences open new research possibilities in the area of statistical treatment of random signals. We realize experiments to test the proposed classification attributes and also consider industrial data from the real life.

Czech name

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Czech description

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Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BA - General mathematics

OECD FORD branch

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Project

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Continuities

Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2010

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Forum Statisticum Slovacum

ISSN

1336-7420

e-ISSN

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Volume of the periodical

7

Issue of the periodical within the volume

5

Country of publishing house

SK - SLOVAKIA

Number of pages

7

Pages from-to

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UT code for WoS article

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EID of the result in the Scopus database

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