The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Numerically stable fast transversal filters for recursive least squares adaptive filtering
Abstract
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, 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, it is shown 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 a complexity of 8N multiplications and additions per time recursion. The results are presented for the complex multichannel joint-process filtering problem.>
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Citations
Cites
Haykin, S. (1986) · Cited by 12,603
(1991) · Springer eBooks · doi:10.1007/978-3-7091-2840-4 · Cited by 5,095
Adaptive filtering, prediction and control
Ioannou, P. (1985) · Automatica · doi:10.1016/0005-1098(85)90014-7 · Cited by 4,480
Theory and Practice of Recursive Identification
Lennart Ljung, A., & Söderström, T. (1983) · Lund University Publications (Lund University) · Cited by 3,989
A First Course in Stochastic Processes
(1975) · Elsevier eBooks · doi:10.1016/c2009-1-28569-8 · Cited by 3,890
Adaptive filtering prediction and control
Goodwin, G. C., & Sin, K. S. (1984) · Cited by 3,400
Morgan, D. (1986) · IEEE Transactions on Acoustics, Speech, and Signal Processing · doi:10.1109/tassp.1986.1164869 · Cited by 1,681
Kronecker Products and Matrix Calculus: With Applications
Graham, A. (1981) · CERN Document Server (European Organization for Nuclear Research) · Cited by 1,630
A multiplicative ergodic theorem. Ljapunov characteristic numbers for dynamical systems.
Oseledec, V. I. (1968) · Medical Entomology and Zoology · Cited by 1,270
Stationary and nonstationary learning characteristics of the LMS adaptive filter
Widrow, B., McCool, J. M., Larimore, M. G., & Johnson, C. R. (1976) · Proceedings of the IEEE · doi:10.1109/proc.1976.10286 · Cited by 1,268
Cited by
Godara, L. C. (1997) · Proceedings of the IEEE · doi:10.1109/5.622504 · Cited by 2,073
A state-space approach to adaptive RLS filtering
Sayed, A. H., & Kailath, T. (1994) · IEEE Signal Processing Magazine · doi:10.1109/79.295229 · Cited by 449
Self-citationEVAM: an eigenvector-based algorithm for multichannel blind deconvolution of input colored signals
Gurelli, M. I., & Nikias, C. L. (1995) · IEEE Transactions on Signal Processing · doi:10.1109/78.365293 · Cited by 196
Metadata
- Authors
- Slock, D. T. M., & Kailath, T.
- Venue
- IEEE Transactions on Signal Processing
- Published
- 1991
- Volume
- 39
- Issue
- 1
- Pages
- 92-114
- ISSN
- 1053-587X (ISSN-L)
- OpenAlex
- W2165653503
- Cited by
- 305
- References
- 22
- FWCI
- 21.49
- Type
- journal article
- Language
- en
- Open access
- closed
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- Slock, D. T. M., & Kailath, T. (1991). Numerically stable fast transversal filters for recursive least squares adaptive filtering. IEEE Transactions on Signal Processing. https://doi.org/10.1109/78.80769
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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