Title :
A least-squares based algorithm for FIR filtering with noisy data
Author_Institution :
Sch. of QMMS, Univ. of Western Sydney, Penrith South, NSW, Australia
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.
Keywords :
FIR filters; adaptive filters; interference suppression; least squares approximations; FIR filter coefficients; FIR filtering; finite impulse response filtering; input noise variance; least-squares based algorithm; noise-induced bias removal; noisy data; noisy input measurements; noisy output measurements; numerical results; output noise variance; Additive noise; Australia; Digital communication; Filtering algorithms; Finite impulse response filter; IIR filters; Noise measurement; Signal processing algorithms; Signal to noise ratio; White noise;
Conference_Titel :
Circuits and Systems, 2003. ISCAS '03. Proceedings of the 2003 International Symposium on
Print_ISBN :
0-7803-7761-3
DOI :
10.1109/ISCAS.2003.1205880
