Abstract
Least-squares algorithms aim at the minimization of the sum of the squares of the difference between the desired signal and the model filter output [1]– [2]. When new samples of the incoming signals are received at every iteration, the solution for the least-squares problem can be computed in recursive form resulting in the recursive least-squares (RLS) algorithms. The conventional version of these algorithms will be the topic of the present chapter.
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© 1997 Springer Science+Business Media New York
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Diniz, P.S.R. (1997). Conventional RLS Adaptive Filter. In: Adaptive Filtering. The Springer International Series in Engineering and Computer Science, vol 399. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-8660-3_5
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DOI: https://doi.org/10.1007/978-1-4419-8660-3_5
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