A delta least squares lattice algorithm for fast sampling

Most shift operator-based adaptive algorithms exhibit poor numerical behavior when the input discrete time process is obtained from a continuous time process by fast sampling. This includes the shift operator based least squares lattice algorithm. We develop a delta least squares lattice algorithm....

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Bibliographic Details
Published in:IEEE transactions on signal processing Vol. 47; no. 9; pp. 2396 - 2406
Main Authors: De, P., Fan, H.H.
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.09.1999
Institute of Electrical and Electronics Engineers
Subjects:
Adaptive algorithm
Adaptive algorithms
Adaptive filters
Algorithms
Applied sciences
Computational complexity
Computer simulation
Deltas
Exact sciences and technology
Information, signal and communications theory
Lattices
Least squares method
Least squares methods
Operators
Resonance light scattering
Sampling
Sampling methods
Sampling, quantization
Signal and communications theory
Signal processing algorithms
Signal sampling
Telecommunications and information theory
Sampled system
Numerical analysis
Adaptive algorithm
Computer simulation
Least squares method
Delta operator
Signal processing
Lattice filter
Computational complexity
Implementation
ISSN:1053-587X
Online Access:Get full text
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Summary:Most shift operator-based adaptive algorithms exhibit poor numerical behavior when the input discrete time process is obtained from a continuous time process by fast sampling. This includes the shift operator based least squares lattice algorithm. We develop a delta least squares lattice algorithm. This algorithm has a low computational complexity compared with the delta Levinson RLS algorithm and shows better numerical properties compared with the shift least squares lattice algorithm under fast sampling. Computer simulations show that the new algorithm also outperforms an existing delta least squares lattice algorithm.
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ISSN:1053-587X
DOI:10.1109/78.782183