A Recursive Parameter Estimation Algorithm for Modeling Signals with Multi-frequencies

In this paper, we focus on the modeling problem of the multi-frequency signals which contain many different frequency components. Based on the Newton search and the measured data, a Newton recursive parameter estimation algorithm is developed to estimate the amplitude, the angular frequency and the...

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Bibliographic Details
Published in:Circuits, systems, and signal processing Vol. 39; no. 8; pp. 4198 - 4224
Main Authors: Xu, Ling, Song, Guanglei
Format: Journal Article
Language:English
Published: New York Springer US 01.08.2020
Springer Nature B.V
Subjects:
Algorithms
Circuits and Systems
Electrical Engineering
Electronics and Microelectronics
Engineering
Hessian matrices
Instrumentation
Mathematical models
Parameter estimation
Performance enhancement
Recursive methods
Short Paper
Signal,Image and Speech Processing
Signal modeling
Parameter estimation
Newton search
Recursive algorithm
Increasing length data
ISSN:0278-081X, 1531-5878
Online Access:Get full text
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Summary:In this paper, we focus on the modeling problem of the multi-frequency signals which contain many different frequency components. Based on the Newton search and the measured data, a Newton recursive parameter estimation algorithm is developed to estimate the amplitude, the angular frequency and the phase of a multi-frequency signal. In order to improve the performance of the identification algorithm, a convergence factor is introduced in the Hessian matrix of the developed Newton recursive method. The numerical examples verify that the proposed algorithm is effective for modeling the multi-frequency sine signals.
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ISSN:0278-081X
1531-5878
DOI:10.1007/s00034-020-01356-3