A finite wordlength analysis of an LMS-Newton adaptive filtering algorithm
نویسندگان
چکیده
AbdvactThe effects of quantization in an LMS-Newton adaptive filtering algorithm are investigated. The algorithm considered uses an optimum convergence factor, that forces the output ayoclteriori error to become zero in each iteration. The prOpagation of errors due to quantization in the internal variables of the algorithm is investigated and a closed-form formula for the excess mean square error due to quantization is derived. Fixed-point arithmetic is assumed throughout. Several \simulations confirm the accuracy of the formulas presented.
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