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Multichannel Fast QRD-RLS Algorithms

  • António L. L. RamosEmail author
  • Stefan Werner
Chapter

Abstract

When considering multichannel adaptive implementations, it is often\break possible to directly apply standard single-channel algorithms to the multichannel problem, e.g., the numerically stable and fast converging QR decomposition recursive least-square (QRD-RLS) algorithm. Even though such a solution would provide fast convergence, it may be computationally too complex due to a large number of coefficients. In order to obtain a computationally efficient solution, RLS-type algorithms specially tailored for the multichannel setup are a good option. This chapter introduces various multichannel fast QRD-RLS (MC-FQRD-RLS) algorithms that can be seen as extensions of the basic single-channel FQRD-RLS algorithms to the case of a multichannel input vector, ∈dexinput vector where it can be assumed that each channel has a time-shift structure. We provide, in a general framework, a comprehensive and up-to-date discussion of the MC-FQRD-RLS algorithms, addressing issues such as derivation, implementation, and comparison in terms of computational complexity.

Keywords

Error Vector Cholesky Factor Lower Triangular Matrix Volterra System Equal Order 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag US 2009

Authors and Affiliations

  1. 1.Buskerud University CollegeKongsbergNorway
  2. 2.Helsinki University of TechnologyHelsinkiFinland

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