Noise Filtering for Big Data Analytics (De Gruyter Series on the Applications of Mathematics in Engineering and Information Sciences, 12) - Hardcover

 
9783110697094: Noise Filtering for Big Data Analytics (De Gruyter Series on the Applications of Mathematics in Engineering and Information Sciences, 12)
Hardcover
ISBN 10: 3110697092 ISBN 13: 9783110697094
Verlag: De Gruyter, 2022

Inhaltsangabe

This book explains how to perform data de-noising, in large scale, with a satisfactory level of accuracy. Three main issues are considered. Firstly, how to eliminate the error propagation from one stage to next stages while developing a filtered model. Secondly, how to maintain the positional importance of data whilst purifying it. Finally, preservation of memory in the data is crucial to extract smart data from noisy big data. If, after the application of any form of smoothing or filtering, the memory of the corresponding data changes heavily, then the final data may lose some important information. This may lead to wrong or erroneous conclusions. But, when anticipating any loss of information due to smoothing or filtering, one cannot avoid the process of denoising as on the other hand any kind of analysis of big data in the presence of noise can be misleading. So, the entire process demands very careful execution with efficient and smart models in order to effectively deal with it.

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Über die Autorin bzw. den Autor

Souvik Bhattacharyya, Koushik Ghosh, University of Burdwan,West Bengal, India.

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Verlag
De Gruyter
Erscheinungsdatum
2022
Sprache
Englisch
ISBN 10 
3110697092
ISBN 13 
9783110697094
Einband
Gebundene Ausgabe
Auflage
1
Anzahl der Seiten
164
Herausgeber
Bhattacharyya Souvik, Ghosh Koushik
Kontakt zum Hersteller
Walter de Gruyter GmbH
info@degruyter.com

Genthiner Straße 13
Berlin
Berlin
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Deutschland