Wavelet-based multiscale statistical process monitoring: A literature review

Autor:	Vivekanand Venkataraman, Rajesh Ganesan, Tapas K. Das
Rok vydání:	2004
Předmět:	Scale analysis (statistics) Audio signal Wavelet Acoustic emission Computer science Scale (chemistry) Process (computing) Mean-shift Data mining computer.software_genre Data type computer Industrial and Manufacturing Engineering
Zdroj:	IIE Transactions. 36:787-806
ISSN:	1545-8830 0740-817X
DOI:	10.1080/07408170490473060
Popis:	Data that represent complex and multivariate processes are well known to be multiscale due to the variety of changes that could occur in a process with different localizations in time and frequency. Examples of changes may include mean shift, spikes, drifts and variance shifts all of which could occur in a process at different times and at different frequencies. Acoustic emission signals arising from machining, images representing MRI scans and musical audio signals are some examples that contain these changes and are not suited for single scale analysis. The recent literature contains several wavelet-decomposition-based multiscale process monitoring approaches including many real life process monitoring applications. These approaches are shown to be effective in handling different data types and, in concept, are likely to perform better than existing single scale approaches. There also exists a vast literature on the theory of wavelet decomposition and other statistical elements of multiscale monitoring ...
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::a854bbc2c0f496cde4926e9d47da2c85 https://doi.org/10.1080/07408170490473060 Zobrazit plný text záznamu Plný text ve formátu PDF Plný text ve formátu HTML
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