Parameter Optimization for Step-Adaptive Approximate Least Squares

Michael Lunglmayr; Mario Huemer

doi:10.1007/978-3-319-27340-2_65

Parameter Optimization for Step-Adaptive Approximate Least Squares

Institute of Signal Processing

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

Abstract

We discuss possible approaches for the adaption of the step width of Step-Adaptive Approximate Least Squares. We present and compare two low complexity and practically feasible adaptation functions whose parameters have been optimized based on computer simulations. We show that by applying these approaches the performance deviation of Step-Adaptive Approximate Least Squares lies within the single percentage range compared to the optimal least squares solution.

Original language	English
Title of host publication	Lecture Notes in Computer Science (LNCS): Computer Aided Systems Theory - EUROCAST 2015
Editors	Franz Pichler, Roberto Moreno-Díaz, Alexis Quesada-Arencibia
Publisher	Springer International Publishing
Pages	521-528
Number of pages	8
Volume	9520
ISBN (Print)	978-3-319-27339-6
DOIs	https://doi.org/10.1007/978-3-319-27340-2_65
Publication status	Published - Dec 2015

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	9520
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Fields of science

202 Electrical Engineering, Electronics, Information Engineering
202022 Information technology
202037 Signal processing

JKU Focus areas

Computation in Informatics and Mathematics
Mechatronics and Information Processing

Access to Document

10.1007/978-3-319-27340-2_65

Cite this

Lunglmayr, M., & Huemer, M. (2015). Parameter Optimization for Step-Adaptive Approximate Least Squares. In F. Pichler, R. Moreno-Díaz, & A. Quesada-Arencibia (Eds.), Lecture Notes in Computer Science (LNCS): Computer Aided Systems Theory - EUROCAST 2015 (Vol. 9520, pp. 521-528). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9520). Springer International Publishing. https://doi.org/10.1007/978-3-319-27340-2_65

Lunglmayr, Michael ; Huemer, Mario. / Parameter Optimization for Step-Adaptive Approximate Least Squares. Lecture Notes in Computer Science (LNCS): Computer Aided Systems Theory - EUROCAST 2015. editor / Franz Pichler ; Roberto Moreno-Díaz ; Alexis Quesada-Arencibia. Vol. 9520 Springer International Publishing, 2015. pp. 521-528 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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title = "Parameter Optimization for Step-Adaptive Approximate Least Squares",

abstract = "We discuss possible approaches for the adaption of the step width of Step-Adaptive Approximate Least Squares. We present and compare two low complexity and practically feasible adaptation functions whose parameters have been optimized based on computer simulations. We show that by applying these approaches the performance deviation of Step-Adaptive Approximate Least Squares lies within the single percentage range compared to the optimal least squares solution.",

author = "Michael Lunglmayr and Mario Huemer",

year = "2015",

month = dec,

doi = "10.1007/978-3-319-27340-2\_65",

language = "English",

isbn = "978-3-319-27339-6",

volume = "9520",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer International Publishing",

pages = "521--528",

editor = "Franz Pichler and Roberto Moreno-D{\'i}az and Alexis Quesada-Arencibia",

booktitle = "Lecture Notes in Computer Science (LNCS): Computer Aided Systems Theory - EUROCAST 2015",

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Lunglmayr, M & Huemer, M 2015, Parameter Optimization for Step-Adaptive Approximate Least Squares. in F Pichler, R Moreno-Díaz & A Quesada-Arencibia (eds), Lecture Notes in Computer Science (LNCS): Computer Aided Systems Theory - EUROCAST 2015. vol. 9520, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9520, Springer International Publishing, pp. 521-528. https://doi.org/10.1007/978-3-319-27340-2_65

Parameter Optimization for Step-Adaptive Approximate Least Squares. / Lunglmayr, Michael ; Huemer, Mario.
Lecture Notes in Computer Science (LNCS): Computer Aided Systems Theory - EUROCAST 2015. ed. / Franz Pichler; Roberto Moreno-Díaz; Alexis Quesada-Arencibia. Vol. 9520 Springer International Publishing, 2015. p. 521-528 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9520).

Research output: Chapter in Book/Report/Conference proceeding › Conference proceedings › peer-review

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AB - We discuss possible approaches for the adaption of the step width of Step-Adaptive Approximate Least Squares. We present and compare two low complexity and practically feasible adaptation functions whose parameters have been optimized based on computer simulations. We show that by applying these approaches the performance deviation of Step-Adaptive Approximate Least Squares lies within the single percentage range compared to the optimal least squares solution.

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VL - 9520

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

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Lunglmayr M , Huemer M. Parameter Optimization for Step-Adaptive Approximate Least Squares. In Pichler F, Moreno-Díaz R, Quesada-Arencibia A, editors, Lecture Notes in Computer Science (LNCS): Computer Aided Systems Theory - EUROCAST 2015. Vol. 9520. Springer International Publishing. 2015. p. 521-528. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-27340-2_65

Parameter Optimization for Step-Adaptive Approximate Least Squares

Abstract

Publication series

Fields of science

JKU Focus areas

Access to Document

Other files and links

Low Complexity Iterative Signal Processing Methods

Cite this

Parameter Optimization for Step-Adaptive Approximate Least Squares

Abstract

Publication series

Fields of science

JKU Focus areas

Access to Document

Other files and links

Projects

Low Complexity Iterative Signal Processing Methods

Cite this