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Noise filtering for big data analytics / edited by Souvik Bhattacharyya and Koushik Ghosh.

DeGruyter DG Plus DeG Package 2022 Part 1 Available online

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Format:
Book
Contributor:
Bhattacharyya, Souvik, editor.
Ghosh, Koushik, editor.
Series:
De Gruyter series on the applications of mathematics in engineering and information sciences ; Volume 12.
De Gruyter series on the applications of mathematics in engineering and information sciences ; Volume 12
Language:
English
Subjects (All):
Big data.
Data mining.
Information filtering systems.
Physical Description:
1 online resource (168 pages) : illustrations
Place of Publication:
Berlin ; Boston : Walter de Gruyter GmbH, [2022]
Summary:
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.
Contents:
Frontmatter
Preface
Contents
About the Editors
Application of discrete domain wavelet filter for signal denoising
Secret sharing scheme in defense and big data analytics
Recent advances in digital image smoothing: A review
Double exponential smoothing and its tuning parameters: A re-exploration
Effect of smoothing on big data governed by polynomial memory
Heteroskedasticity in panel data: A big challenge to data filtering
Importance and use of digital filters in digital image processing
Smart filter and smoothing: A new approach of data denoising
Acknowledgement
Index
Notes:
Description based upon print version of record.
Description based on print version record.
Includes bibliographical references and index.
ISBN:
3-11-069721-1

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