Noise filtering for big data analytics
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 import...
| Other Authors: | , |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Berlin ; Boston:
De Gruyter,
[2022]
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| Series: | De Gruyter series on the applications of mathematics in engineering and information sciences ;
v. 12. |
| Subjects: | |
| Online Access: | EBSCOhost Перейти в каталог НБ ТГУ |
Table of 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.