Title :
Convergence analysis of an adaptive filter equipped with the sign-sign algorithm
Author_Institution :
Mil. Tech. Coll., Cairo, Egypt
fDate :
10/1/1995 12:00:00 AM
Abstract :
Convergence with probability 1 of the sign-sign algorithm with a decreasing step size is proven when it is used in adaptive plant identification. The plant input and plant noise are assumed stationary and M-dependent. The assumptions do not pose any upper bound on the memory, M, of the plant input and plant noise, and hence, they allow arbitrarily strong correlation in these signals. A main interest of the paper is that it provides a condition of persistent excitation of the algorithm. Examples satisfying this condition are provided
Keywords :
adaptive estimation; adaptive filters; convergence; identification; probability; adaptive filter; adaptive plant identification; convergence analysis; decreasing step size; persistent excitation condition; sign-sign algorithm; Adaptive filters; Algorithm design and analysis; Convergence; Data analysis; Differential equations; Estimation error; Filtering algorithms; Least squares approximation; Upper bound; Working environment noise;
Journal_Title :
Automatic Control, IEEE Transactions on
