Noise Filtering for Big Data Analytics

Ahead of Publication Published by De Gruyter 2022

Noise Filtering for Big Data Analytics

Edited by: Souvik Bhattacharyya and Koushik Ghosh

Volume 12 in the series De Gruyter Series on the Applications of Mathematics in Engineering and Information Sciences

Overview

About this book

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.

Author information

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

Topics

(Deutsch)

Language: English
Publisher: De Gruyter
Audience: researchers, students and experienced professionals
Pages
- Front matter: 8
- Main content: 156
Illustrations
- Illustrations: 75
- Tables: 12
Keywords: Angewandte Mathematik; Big Data; Künstliche Intelligenz; Maschinelles Lernen

eBook

Planned Publication: June 7, 2022
ISBN: 9783110697216

Hardcover

Planned Publication: June 21, 2022
ISBN: 9783110697094