Separable Synchronous Multi-Innovation Gradient-Based Iterative Signal Modeling From On-Line Measurements

This article is aimed to study the modeling problems of combinational signals or periodic signals. To overcome the computation complexity of modeling the signals with plenty of characteristic parameters, a parameter separation scheme is developed based on the different characteristic of the signals...

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Veröffentlicht in:IEEE transactions on instrumentation and measurement Jg. 71; S. 1 - 13
Hauptverfasser: Xu, Ling, Ding, Feng, Zhu, Quanmin
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 2022
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithms
Complexity
Computational modeling
Coupling
Data models
Data sampling
Estimation
Frequency estimation
Gradient search
hierarchical identification
Innovations
iterative algorithm
Iterative algorithms
Iterative methods
Mathematical models
multi-innovation identification
parameter estimation
Parameters
Real-time systems
signal modeling
Sine waves
Square waves
Technological innovation
ISSN:0018-9456, 1557-9662
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Zusammenfassung:This article is aimed to study the modeling problems of combinational signals or periodic signals. To overcome the computation complexity of modeling the signals with plenty of characteristic parameters, a parameter separation scheme is developed based on the different characteristic of the signals to be modeled. For the purpose of achieving high-accuracy performance and reducing complexity, two multi-innovation gradient-based iterative (MIGI) subalgorithms are presented by means of gradient search. In terms of the phenomenon that the coupling parameters lead to the inability of algorithms, a separable synchronous (SS) interactive estimation method is proposed to eliminate the coupling parameters and perform the signal modeling algorithm in accordance with the hierarchical principle. By means of simulation experiments, the proposed SS iterative signal modeling algorithm based on the moving batch data is used for estimating a power signal with three sine waves and a periodic square wave signal. The results demonstrate the effectiveness of the proposed method for modeling the combinational signals with multiple frequencies and other periodic signals. Since the proposed method combines real-time data sampling and iterative estimation, it can be used for on-line identification.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0018-9456
1557-9662
DOI:10.1109/TIM.2022.3154797