Fast adaptive identification of stable innovation filters

The adaptive identification of the impulse response of an innovation filter is considered. The impulse response is a finite sum of known basis functions with unknown coefficients. These unknown coefficients are estimated using a pseudolinear regression. This estimate is implemented using a square ro...

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Bibliographic Details
Published in:IEEE transactions on signal processing 1997-10, Vol.45 (10), p.2616-2619
Main Authors: Mullhaupt, A.P., Riedel, K.S.
Format: Article
Language:English
Subjects:
Adaptive filters
Applied sciences
Detection, estimation, filtering, equalization, prediction
Exact sciences and technology
Information, signal and communications theory
MIMO
Predictive models
Recursive estimation
Signal and communications theory
Signal, noise
State estimation
State-space methods
Stochastic processes
System identification
Technological innovation
Telecommunications and information theory
Vectors
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Summary:The adaptive identification of the impulse response of an innovation filter is considered. The impulse response is a finite sum of known basis functions with unknown coefficients. These unknown coefficients are estimated using a pseudolinear regression. This estimate is implemented using a square root algorithm based on a displacement rank structure. When the initial conditions have low displacement rank, the filter update is O(n). If the filter architecture is chosen to be triangular input balanced (TIB), the estimation problem is well conditioned, and a simple, low-rank initialization is available.
ISSN:1053-587X
1941-0476
DOI:10.1109/78.640733