Title :
Analysis of the Gradient-Descent Total Least-Squares Adaptive Filtering Algorithm
Author :
Arablouei, Reza ; Werner, Stefan ; Dogancay, Kutluyil
Author_Institution :
Inst. for Telecommun. Res., Univ. of South Australia, Mawson Lakes, SA, Australia
Abstract :
The gradient-descent total least-squares (GD-TLS) algorithm is a stochastic-gradient adaptive filtering algorithm that compensates for error in both input and output data. We study the local convergence of the GD-TLS algoritlun and find bounds for its step-size that ensure its stability. We also analyze the steady-state performance of the GD-TLS algorithm and calculate its steady-state mean-square deviation. Our steady-state analysis is inspired by the energy-conservation-based approach to the performance analysis of adaptive filters. The results predicted by the analysis show good agreement with the simulation experiments.
Keywords :
adaptive filters; least squares approximations; stochastic processes; energy-conservation; gradient-descent total least-squares algorithm; steady-state analysis; steady-state mean-square deviation; stochastic-gradient adaptive filtering algorithm; Adaptive filters; Algorithm design and analysis; Signal processing algorithms; Stability criteria; Steady-state; Vectors; Adaptive filtering; Rayleigh quotient; mean-square deviation; performance analysis; stability; total least-squares;
Journal_Title :
Signal Processing, IEEE Transactions on
DOI :
10.1109/TSP.2014.2301135
