Denoising and Averaging Techniques for Electrophysiological Data

Matthias Ihrke; Hecke Schrobsdorff; J. Michael Herrmann

doi:10.1007/978-0-387-93797-7_9

Denoising and Averaging Techniques for Electrophysiological Data

Matthias Ihrke, Hecke Schrobsdorff, J. Michael Herrmann

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Neurophysiological signals are often corrupted by noise that is significantly stronger than the signal itself. In electroencephalographic (EEG) data this may amount to figures of −25 dB (Flexer, 2000), for electromyography (EMG) or functional magnetic resonance imaging (fMRI) the situation is similar. The problem of the recovery of information under noise has been dealt with extensively in the literature of signal and image processing (Whalen, 1971; Castleman, 1996).

Original language	English
Title of host publication	Coordinated Activity in the Brain
Subtitle of host publication	Measurements and Relevance to Brain Function and Behavior
Editors	Perez Jose Luis Velazquez, Richard Wennberg
Place of Publication	New York, NY
Publisher	Springer
Pages	165-189
Number of pages	25
ISBN (Electronic)	978-0-387-93797-7
ISBN (Print)	978-0-387-93796-0
DOIs	https://doi.org/10.1007/978-0-387-93797-7_9
Publication status	Published - 2009

Publication series

Name	Springer Series in Computational Neuroscience
Publisher	Springer New York
Volume	2
ISSN (Print)	2197-1900

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10.1007/978-0-387-93797-7_9

http://link.springer.com/chapter/10.1007/978-0-387-93797-7_9

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Ihrke, M., Schrobsdorff, H., & Herrmann, J. M. (2009). Denoising and Averaging Techniques for Electrophysiological Data. In P. J. L. Velazquez, & R. Wennberg (Eds.), Coordinated Activity in the Brain: Measurements and Relevance to Brain Function and Behavior (pp. 165-189). (Springer Series in Computational Neuroscience; Vol. 2). Springer. https://doi.org/10.1007/978-0-387-93797-7_9

Ihrke, Matthias ; Schrobsdorff, Hecke ; Herrmann, J. Michael. / Denoising and Averaging Techniques for Electrophysiological Data. Coordinated Activity in the Brain: Measurements and Relevance to Brain Function and Behavior. editor / Perez Jose Luis Velazquez ; Richard Wennberg. New York, NY : Springer, 2009. pp. 165-189 (Springer Series in Computational Neuroscience).

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title = "Denoising and Averaging Techniques for Electrophysiological Data",

abstract = "Neurophysiological signals are often corrupted by noise that is significantly stronger than the signal itself. In electroencephalographic (EEG) data this may amount to figures of −25 dB (Flexer, 2000), for electromyography (EMG) or functional magnetic resonance imaging (fMRI) the situation is similar. The problem of the recovery of information under noise has been dealt with extensively in the literature of signal and image processing (Whalen, 1971; Castleman, 1996).",

author = "Matthias Ihrke and Hecke Schrobsdorff and Herrmann, {J. Michael}",

year = "2009",

doi = "10.1007/978-0-387-93797-7_9",

language = "English",

isbn = "978-0-387-93796-0",

series = "Springer Series in Computational Neuroscience",

publisher = "Springer",

pages = "165--189",

editor = "Velazquez, {Perez Jose Luis} and Richard Wennberg",

booktitle = "Coordinated Activity in the Brain",

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Ihrke, M, Schrobsdorff, H & Herrmann, JM 2009, Denoising and Averaging Techniques for Electrophysiological Data. in PJL Velazquez & R Wennberg (eds), Coordinated Activity in the Brain: Measurements and Relevance to Brain Function and Behavior. Springer Series in Computational Neuroscience, vol. 2, Springer, New York, NY, pp. 165-189. https://doi.org/10.1007/978-0-387-93797-7_9

Denoising and Averaging Techniques for Electrophysiological Data. / Ihrke, Matthias; Schrobsdorff, Hecke; Herrmann, J. Michael.
Coordinated Activity in the Brain: Measurements and Relevance to Brain Function and Behavior. ed. / Perez Jose Luis Velazquez; Richard Wennberg. New York, NY: Springer, 2009. p. 165-189 (Springer Series in Computational Neuroscience; Vol. 2).

Research output: Chapter in Book/Report/Conference proceeding › Chapter

TY - CHAP

T1 - Denoising and Averaging Techniques for Electrophysiological Data

AU - Ihrke, Matthias

AU - Schrobsdorff, Hecke

AU - Herrmann, J. Michael

PY - 2009

Y1 - 2009

N2 - Neurophysiological signals are often corrupted by noise that is significantly stronger than the signal itself. In electroencephalographic (EEG) data this may amount to figures of −25 dB (Flexer, 2000), for electromyography (EMG) or functional magnetic resonance imaging (fMRI) the situation is similar. The problem of the recovery of information under noise has been dealt with extensively in the literature of signal and image processing (Whalen, 1971; Castleman, 1996).

AB - Neurophysiological signals are often corrupted by noise that is significantly stronger than the signal itself. In electroencephalographic (EEG) data this may amount to figures of −25 dB (Flexer, 2000), for electromyography (EMG) or functional magnetic resonance imaging (fMRI) the situation is similar. The problem of the recovery of information under noise has been dealt with extensively in the literature of signal and image processing (Whalen, 1971; Castleman, 1996).

U2 - 10.1007/978-0-387-93797-7_9

DO - 10.1007/978-0-387-93797-7_9

M3 - Chapter

SN - 978-0-387-93796-0

T3 - Springer Series in Computational Neuroscience

SP - 165

EP - 189

BT - Coordinated Activity in the Brain

A2 - Velazquez, Perez Jose Luis

A2 - Wennberg, Richard

PB - Springer

CY - New York, NY

ER -

Denoising and Averaging Techniques for Electrophysiological Data

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