Title :
Tracking properties of vector space adaptive filters
Author :
Williamson, Geoffrey A.
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA
Abstract :
Tracking properties are considered for adaptive filters which are adjusted within a vector space of filtering operations. For a given vector space of systems, the adaptive filter structure is determined by a choice of basis for the vector space. Basis dependent expressions are developed for the asymptotic mean square error (MSE) under least-mean-square (LMS) and recursive-least-square (RLS) adaptation, when the optimal filter specification is subject to constant drift. For the idealized setting considered, it is shown that the minimum achievable MSE using LMS adaptation is less than or equal to that achievable under RLS adaptation
Keywords :
adaptive filters; filtering and prediction theory; least squares approximations; parameter estimation; signal processing; tracking; LMS adaptation; MSE; RLS adaptation; asymptotic mean square error; basis dependent expressions; least-mean-square; recursive-least-square; tracking properties; vector space adaptive filters; Adaptive filters; Costs; Finite impulse response filter; Least squares approximation; Least squares methods; Linear systems; Mean square error methods; Resonance light scattering; Space technology; Vectors;
Conference_Titel :
Signals, Systems and Computers, 1992. 1992 Conference Record of The Twenty-Sixth Asilomar Conference on
Conference_Location :
Pacific Grove, CA
Print_ISBN :
0-8186-3160-0
DOI :
10.1109/ACSSC.1992.269263
