Adaptive signal processing
Adaptive filter theory (2nd ed.)
Adaptive filter theory (2nd ed.)
Matrix computations (3rd ed.)
Advances in Network and Acoustic Echo Cancellation
Advances in Network and Acoustic Echo Cancellation
Derivation of Excess Mean-Square Error for Affine Projection Algorithms Using the Condition Number
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
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The recursive least squares (RLS) algorithm is one of the most popular adaptive algorithms that can be found in the literature, due to the fact that it is easily and exactly derived from the normal equations. In this paper, we give another interpretation of the RLS algorithm and show the importance of linear interpolation error energies in the RLS structure. We also give a very efficient way to recursively estimate the condition number of the input signal covariance matrix thanks to fast versions of the RLS algorithm. Finally, we quantify the misalignment of the RLS algorithm with respect to the condition number.