Title :
Analysis of LMS-Newton adaptive filtering algorithms with variable convergence factor
Author :
Diniz, Paulo S R ; De Campos, Marcello L R ; Antoniou, Andreas
Author_Institution :
Dept. of Electron., Federal Univ. of Rio de Janeiro, Brazil
fDate :
3/1/1995 12:00:00 AM
Abstract :
An analysis of two LMS-Newton adaptive filtering algorithms with variable convergence factor is presented. The relations of these algorithms with the conventional recursive least-squares algorithm are first addressed. Their performance in stationary and nonstationary environments is then studied and closed-form formulas for the excess mean-square error (MSE) are derived. The paper deals, in addition, with the effects of roundoff errors for the case of fixed-point arithmetic. Specifically, closed-form formulas for the excess MSE caused by quantization are obtained. The paper concludes with experimental results that demonstrate the validity of the analysis presented
Keywords :
Newton method; adaptive filters; adaptive signal processing; convergence of numerical methods; digital arithmetic; filtering theory; least mean squares methods; quantisation (signal); roundoff errors; LMS-Newton adaptive filtering algorithms; MSE; closed-form formulas; experimental results; fixed-point arithmetic; mean-square error; nonstationary environments; performance; quantization; recursive least-squares algorithm; roundoff errors; stationary environments; variable convergence factor; Adaptive filters; Algorithm design and analysis; Convergence; Filtering algorithms; Fixed-point arithmetic; Iterative algorithms; Least squares approximation; Resonance light scattering; Signal processing algorithms; Statistics;
Journal_Title :
Signal Processing, IEEE Transactions on
