A Rapid Introduction to Adaptive Filtering
In this book, the authors provide insights into the basics of adaptive filtering, which are particularly useful for students taking their first steps into this field. They start by studying the problem of minimum mean-square-error filtering, i.e., Wiener filtering. Then, they analyze iterative metho...
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| Главные авторы: | , |
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| Соавтор: | |
| Формат: | Электронный ресурс eКнига |
| Язык: | English |
| Опубликовано: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2013.
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| Редактирование: | 1st ed. 2013. |
| Серии: | SpringerBriefs in Electrical and Computer Engineering,
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| Предметы: | |
| Online-ссылка: | https://doi.org/10.1007/978-3-642-30299-2 |
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Оглавление:
- Wiener Filtering and examples
- Steepest descent procedure
- Stochastic gradient adaptive filtering: LMS (Least Mean Squares), NLMS (Normalized Mean Squares)
- Sign-error algorithm, APA (Affine Projection Algorithms)
- Convergence results
- Applications
- LS (Least Squares) and RLS (Recursive Least Squares)
- Computational complexity and fast implementations
- Applications.