Adaptive Segmentation with Successive Windows
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F14%3A00223534" target="_blank" >RIV/68407700:21230/14:00223534 - isvavai.cz</a>
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Adaptive Segmentation with Successive Windows
Original language description
Segmentation is an important part of signal processing and it significantly influences on a further analysis quality. Adaptive segmentation based on sliding windows has a good performance characteristic and can work online. In the paper fractal dimension, frequency-weighted energy (nonlinear energy operator) and measure M of the Varri method were calculated as signal characteristics in a successive window and results were used as features for adaptive segmentation. Time performance and segmentation quality were compared for these algorithms. For evaluation of segmentation quality, artificial signal, signal with artefacts and normal EEG signal were used. Also a real long-term signal was tested.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
JC - Computer hardware and software
OECD FORD branch
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Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2014
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of BioDat 2014 - Conference on Advanced Methods of Biological Data and Signal Processing
ISBN
978-80-01-05624-0
ISSN
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e-ISSN
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Number of pages
7
Pages from-to
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Publisher name
ČVUT
Place of publication
Praha
Event location
Praha
Event date
Nov 20, 2014
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
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