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• W1982862833 abstract "Steepest descent gradient algorithms for unbiased equation error adaptive infinite impulse response (IIR) filtering are analyzed collectively for both the total least squares and mixed least squares-total least squares framework. These algorithms have a monic normalization that allows for a direct filtering implementation. We show that the algorithms converge to the desired filter coefficient vector. We achieve the convergence result by analyzing the stability of the equilibrium points and demonstrate that only the desired solution is locally stable. Additionally, we describe a region of initialization under which the algorithm converges to the desired solution. We derive the results using interlacing relationships between the eigenvalues of the data correlation matrices and their respective Schur complements. Finally, we illustrate the performance of these new approaches through simulation." @default.
• W1982862833 created "2016-06-24" @default.
• W1982862833 creator A5006211510 @default.
• W1982862833 creator A5081569135 @default.
• W1982862833 date "2004-12-01" @default.
• W1982862833 modified "2023-09-30" @default.
• W1982862833 title "Analysis of Gradient Algorithms for TLS-Based Adaptive IIR Filters" @default.
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• W1982862833 doi "https://doi.org/10.1109/tsp.2004.837408" @default.
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