ISSN:
1572-9265
Keywords:
AMS(MOS)
;
15A18
;
65F10
;
65F20
;
65F35
;
Adaptive methods
;
condition estimation
;
control
;
downdating
;
eigenvalues
;
Lanczos methods
;
matrix modifications
;
recursive least squares
;
signal processing
;
singular values
;
updating
Source:
Springer Online Journal Archives 1860-2000
Topics:
Computer Science
,
Mathematics
Notes:
Abstract Estimates for the condition number of a matrix are useful in many areas of scientific computing, including: recursive least squares computations, optimization, eigenanalysis, and general nonlinear problems solved by linearization techniques where matrix modification techniques are used. The purpose of this paper is to propose anadaptiveLanczosestimator scheme, which we callale, for tracking the condition number of the modified matrix over time. Applications to recursive least squares (RLS) computations using the covariance method with sliding data windows are considered.ale is fast for relatively smalln-parameter problems arising in RLS methods in control and signal processing, and is adaptive over time, i.e., estimates at timet are used to produce estimates at timet+1. Comparisons are made with other adaptive and non-adaptive condition estimators for recursive least squares problems. Numerical experiments are reported indicating thatale yields a very accurate recursive condition estimator.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1007/BF02145580
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