Title :
Performance analysis of adaptive filters equipped with the dual sign algorithm
Author_Institution :
Dept. of Electr. Eng., Utah Univ., Salt Lake City, UT, USA
fDate :
1/1/1991 12:00:00 AM
Abstract :
A convergence analysis for stochastic gradient adaptive filters equipped with the dual sign algorithm (DSA) is presented. Expressions for the mean and mean-squared values of the coefficient misalignment vector are derived under the assumption that the input signal is Gaussian. The main differences between the current analysis and previous analyses are: (1) the present analysis is valid for arbitrary autocorrelation matrices, and (2) the analysis does not approximate the behavior for the DSA as switching between two sign algorithms a certain amount of time after the DSA is initialized. A simulation example comparing the analytical results with empirical ones is presented and the two curves show excellent agreement with each other
Keywords :
adaptive filters; convergence; filtering and prediction theory; signal processing; Gaussian input signal; adaptive filters; arbitrary autocorrelation matrices; coefficient misalignment vector; convergence analysis; dual sign algorithm; performance analysis; stochastic gradient filters; Adaptive filters; Algorithm design and analysis; Computational complexity; Computational modeling; Convergence; Degradation; Performance analysis; Signal analysis; Steady-state; Switches;
Journal_Title :
Signal Processing, IEEE Transactions on