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...
Gorde:
| Egile Nagusiak: | , |
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| Erakunde egilea: | |
| Formatua: | Baliabide elektronikoa eBook |
| Hizkuntza: | English |
| Argitaratua: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2013.
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| Edizioa: | 1st ed. 2013. |
| Saila: | SpringerBriefs in Electrical and Computer Engineering,
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| Gaiak: | |
| Sarrera elektronikoa: | https://doi.org/10.1007/978-3-642-30299-2 |
| Etiketak: |
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Aurkibidea:
- 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.