The sub-recursive least squares (sub-rls) algorithm estimates the coefficients of adaptive filter under the least squares (LS) criterion, however, does not require the calculation of inverse matrix. The sub-rls algori...
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The sub-recursive least squares (sub-rls) algorithm estimates the coefficients of adaptive filter under the least squares (LS) criterion, however, does not require the calculation of inverse matrix. The sub-rls algorithm, based on the different principle from the rlsalgorithm, still provides a convergence property similar to that of the rlsalgorithm. This paper first rewrites the convergence condition of the sub-rls algorithm, and then proves that the convergence property of the sub-rls algorithm successively approximates that of the rlsalgorithm on the convergence condition.
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