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.
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Ramos, A.L.L., Werner, S. (2009). Multichannel Fast QRD-RLS Algorithms. In: QRD-RLS Adaptive Filtering. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09734-3_6
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DOI: https://doi.org/10.1007/978-0-387-09734-3_6
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