Optimization of weighting factors in the peak matched multiple window method

Maria Sandsten

doi:10.1109/ICASSP.1997.604795

Optimization of weighting factors in the peak matched multiple window method

Maria Sandsten

Mathematical Statistics

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

Abstract

Peak matched multiple windows are found as the Karhunen-Loeve basis functions of a predefined peaked spectrum. With a penalty function, an optimization procedure can be constrained with resulting control of sidelobes. Weighting factors, included in the averaging of the periodograms, can be designed to fulfill certain constraints. Desirable properties are low variance and small bias. This paper presents a discussion of minimization of variance at the peak compared with the optimization that also include the neighbourhood of the peak.

Original language	English
Title of host publication	1997 IEEE International Conference on Acoustics, Speech, and Signal Processing
Publisher	IEEE - Institute of Electrical and Electronics Engineers Inc.
ISBN (Print)	0-8186-7919-0
DOIs	https://doi.org/10.1109/ICASSP.1997.604795
Publication status	Published - 1997
Event	1997 IEEE International Conference on Acoustics, Speech, and Signal Processing - Munich, Germany Duration: 1997 Apr 21 → 1997 Apr 24

Conference

Conference	1997 IEEE International Conference on Acoustics, Speech, and Signal Processing
Country/Territory	Germany
City	Munich
Period	1997/04/21 → 1997/04/24

Subject classification (UKÄ)

Signal Processing

Access to Document

10.1109/ICASSP.1997.604795

Cite this

@inproceedings{98ef26fcd8ec49c3bacd0df423de5fcf,

title = "Optimization of weighting factors in the peak matched multiple window method",

abstract = "Peak matched multiple windows are found as the Karhunen-Loeve basis functions of a predefined peaked spectrum. With a penalty function, an optimization procedure can be constrained with resulting control of sidelobes. Weighting factors, included in the averaging of the periodograms, can be designed to fulfill certain constraints. Desirable properties are low variance and small bias. This paper presents a discussion of minimization of variance at the peak compared with the optimization that also include the neighbourhood of the peak.",

author = "Maria Sandsten",

year = "1997",

doi = "10.1109/ICASSP.1997.604795",

language = "English",

isbn = "0-8186-7919-0",

booktitle = "1997 IEEE International Conference on Acoustics, Speech, and Signal Processing",

publisher = "IEEE - Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

note = "1997 IEEE International Conference on Acoustics, Speech, and Signal Processing ; Conference date: 21-04-1997 Through 24-04-1997",

}

Sandsten, M 1997, Optimization of weighting factors in the peak matched multiple window method. in 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE - Institute of Electrical and Electronics Engineers Inc., 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing , Munich, Germany, 1997/04/21. https://doi.org/10.1109/ICASSP.1997.604795

TY - GEN

T1 - Optimization of weighting factors in the peak matched multiple window method

AU - Sandsten, Maria

PY - 1997

Y1 - 1997

N2 - Peak matched multiple windows are found as the Karhunen-Loeve basis functions of a predefined peaked spectrum. With a penalty function, an optimization procedure can be constrained with resulting control of sidelobes. Weighting factors, included in the averaging of the periodograms, can be designed to fulfill certain constraints. Desirable properties are low variance and small bias. This paper presents a discussion of minimization of variance at the peak compared with the optimization that also include the neighbourhood of the peak.

AB - Peak matched multiple windows are found as the Karhunen-Loeve basis functions of a predefined peaked spectrum. With a penalty function, an optimization procedure can be constrained with resulting control of sidelobes. Weighting factors, included in the averaging of the periodograms, can be designed to fulfill certain constraints. Desirable properties are low variance and small bias. This paper presents a discussion of minimization of variance at the peak compared with the optimization that also include the neighbourhood of the peak.

UR - https://www.scopus.com/pages/publications/0030702237

U2 - 10.1109/ICASSP.1997.604795

DO - 10.1109/ICASSP.1997.604795

M3 - Paper in conference proceeding

SN - 0-8186-7919-0

BT - 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing

PB - IEEE - Institute of Electrical and Electronics Engineers Inc.

T2 - 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing

Y2 - 21 April 1997 through 24 April 1997

ER -

Optimization of weighting factors in the peak matched multiple window method

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Statistical Signal Processing Group

Cite this

Optimization of weighting factors in the peak matched multiple window method

Abstract

Conference

Subject classification (UKÄ)

Access to Document

Other files and links

Fingerprint

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Statistical Signal Processing Group

Cite this