Abstract
This chapter deals with the basic concepts used in the recursive least-squares (RLS) algorithms employing conventional and inverse QR decomposition. The methods of triangularizing the input data matrix and the meaning of the internal variables of these algorithms are emphasized in order to provide details of their most important relations. The notation and variables used herein will be exactly the same used in the previous introductory chapter. For clarity, all derivations will be carried out using real variables and the final presentation of the algorithms (tables and pseudo-codes) will correspond to their complex-valued versions.
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Apolinário, J.A., Miranda, M.D. (2009). Conventional and Inverse QRD-RLS Algorithms. In: QRD-RLS Adaptive Filtering. Springer, Boston, MA. https://doi.org/10.1007/978-0-387-09734-3_3
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DOI: https://doi.org/10.1007/978-0-387-09734-3_3
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