fast transversal filter
error
Numerically Stable Fast Transversal Filters for Recursive Least-Squares Adaptive Filtering
false
chapters
chapter
instability
results
1991-01-01
exponential weighting
2022-05-20T07:48
In this paper, a solution is proposed to the long-standing problem of the numerical instability of Fast Recursive Least-Squares Transversal Filter (FTF) algorithms with exponential weighting, which is an important class of algorithms for adaptive filtering. A framework for the analysis of the error propagation in FTF algorithms is first developed; within this framework, we show that the computationally most efficient 7N form is exponentially unstable. However, by introducing redundancy into this algorithm, feedback of numerical errors becomes possible; a judicious choice of the feedback gains then leads to a numerically stable FTF algorithm with complexity 9N. The results are presented for the complex multichannel joint-process filtering problem.
FTF algorithm
filtering
filtering problem
problem
filter
solution
adaptive filtering
error propagation
https://scigraph.springernature.com/explorer/license/
feedback
recursive least squares adaptive filtering
weighting
1991
605-615
feedback gains
fast recursive least-squares transversal filters
form
numerical instability
class
analysis
important class
framework
judicious choice
transversal filter
en
gain
https://doi.org/10.1007/978-3-642-75536-1_49
algorithm
redundancy
choice
paper
numerical errors
propagation
least squares adaptive filtering
Slock
Dirk T. M.
Thomas
Kailath
Information and Computing Sciences
Department of Electrical Engineering Information Systems Laboratory, Stanford University, 94305, Stanford, CA, USA
Department of Electrical Engineering Information Systems Laboratory, Stanford University, 94305, Stanford, CA, USA
Paul
Van Dooren
Computation Theory and Mathematics
Springer Nature - SN SciGraph project
doi
10.1007/978-3-642-75536-1_49
Golub
Gene H.
Springer Nature
dimensions_id
pub.1052265355
978-3-642-75536-1
978-3-642-75538-5
Numerical Linear Algebra, Digital Signal Processing and Parallel Algorithms