QRD-RLS Adaptive Filtering

QRD-RLS Adaptive Filtering covers some of the most recent developments as well as the basic concepts for a complete understanding of the QRD-RLS-based adaptive filtering algorithms. It presents this research with a clear historical perspective which highlights the underpinning theory and common moti...

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Xehetasun bibliografikoak
Egile nagusia: Apolinário, José Antonio (Argitaratzailea)
Formatua: Livre numérique
Hizkuntza:Anglais
Argitaratua: New York, NY : Springer US 2009.
Cham : Springer Nature
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100 1 |a Apolinário, José Antonio. 
245 1 0 |a QRD-RLS Adaptive Filtering   |c edited by José Antonio Apolinário. 
256 |a Données textuelles 
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260 |a Cham :  |b Springer Nature,  |c 2009. 
500 |a Archives Springer e-books (Licence nationale) 
500 |a Archives Springer e-books (Licence nationale) 
505 1 |a QR Decomposition An Annotated Bibliography to Adaptive Filters Conventional and Inverse QRD-RLS Algorithms Fast QRD-RLS Algorithms QRD Least-Squares Lattice Algorithms Multichannel Fast QRD-RLS Algorithms Householder-Based RLS Algorithms Numerical Stability Properties Finite and Infinite-Precision Properties of QRD-RLS Algorithms On Pipelined Implementations of QRD-RLS Adaptive Filters Weight Extraction of Fast QRD-RLS Algorithms Linear Constrained QRD-Based Algorithm 
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506 |a Conditions particulières de réutilisation pour les bénéficiaires des licences nationales. https://www.licencesnationales.fr/springer-nature-ebooks-contrat-licence-ln-2017 
520 |a QRD-RLS Adaptive Filtering covers some of the most recent developments as well as the basic concepts for a complete understanding of the QRD-RLS-based adaptive filtering algorithms. It presents this research with a clear historical perspective which highlights the underpinning theory and common motivating factors that have shaped the subject. The material is divided into twelve chapters, going from fundamentals to more advanced aspects. Different algorithms are derived and presented, including basic, fast, lattice, multichannel and constrained versions. Important issues, such as numerical stability, performance in finite precision environments and VLSI oriented implementations are also addressed. All algorithms are derived using Givens rotations, although one chapter deals with implementations using Householder reflections. QRD-RLS Adaptive Filtering is a useful reference for engineers and academics in the field of adaptive filtering 
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