Abstract
This paper is concerned with finite impulse response (FIR) filtering with noisy input and output measurements. A new least-squares (LS) based algorithm is proposed to estimate the FIR filter coefficients. It is shown that the noise-induced bias can be removed once the variances of the input noise and output noise are obtained. A simple procedure is presented for estimating these variances by taking advantage of the FIR filter structure. The proposed LS based algorithm is easy to implement. Numerical results that illustrate the attractive properties of the new FIR filtering algorithm are presented.
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