Title :
A robust recursive least squares algorithm
Author :
Chansarkar, Mangesh M. ; Desai, Uday B.
Author_Institution :
SSA Aerospace Systems Pvt. Ltd., Bangalore, India
fDate :
7/1/1997 12:00:00 AM
Abstract :
A new algorithm is developed, which guarantees the normalized bias in the weight vector due to persistent and bounded data perturbations to be bounded. Robustness analysis for this algorithm has been presented. An approximate recursive implementation is also proposed. It is termed as the robust recursive least squares (RRLS) algorithm since it resembles the RLS algorithm in its structure and is robust with respect to persistent bounded data perturbation. Simulation results are presented to illustrate the efficacy of the RRLS algorithm
Keywords :
least squares approximations; recursive filters; signal processing; normalized bias; persistent bounded data perturbation; robust recursive least squares algorithm; simulation; weight vector; Algorithm design and analysis; Error analysis; Filters; Least squares approximation; Least squares methods; Performance analysis; Resonance light scattering; Robustness; Roundoff errors; Signal processing algorithms;
Journal_Title :
Signal Processing, IEEE Transactions on