Title :
Comparison of DC offset effects in four LMS adaptive algorithms
Author :
Shoval, Ayal ; Johns, David A. ; Snelgrove, W. Martin
Author_Institution :
Dept. of Electr. & Comput. Eng., Toronto Univ., Ont., Canada
fDate :
3/1/1995 12:00:00 AM
Abstract :
It is well known that DC offsets degrade the performance of analog adaptive filters. In this paper, the effects of DC offsets on four variations of the stochastic gradient algorithm are analyzed. Assuming a Gaussian probability distribution for the input signal and error signal, the output mean squared error (MSE) performance in the presence of DC offsets is evaluated for each of the algorithms. The theoretical work is compared with computer simulations and the results, together with convergence properties of each of the algorithms and their respective hardware requirements, are used in selecting the most appropriate algorithm. Although a Gaussian input distribution is assumed, it may reasonably be inferred that the critical results obtained should also hold for other input distributions
Keywords :
Gaussian distribution; adaptive filters; adaptive signal processing; convergence; filtering theory; least mean squares methods; stochastic processes; DC offset effects; Gaussian probability distribution; LMS adaptive algorithms; convergence properties; mean squared error; output MSE performance; stochastic gradient algorithm; Adaptive algorithm; Adaptive filters; Algorithm design and analysis; Computer errors; Computer simulation; Convergence; Degradation; Least squares approximation; Probability distribution; Stochastic processes;
Journal_Title :
Circuits and Systems II: Analog and Digital Signal Processing, IEEE Transactions on
