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Digital signal processing for denois...

Southern Connecticut State University.

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Digital signal processing for denoising electrophysiological data.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Digital signal processing for denoising electrophysiological data./
Author:	Peng, Hui.
Description:	123 p.
Notes:	Adviser: Hrvoje Podnar.
Contained By:	Masters Abstracts International46-05.
Subject:	Computer Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1452165
ISBN:	9780549481553

Digital signal processing for denoising electrophysiological data.
Peng, Hui.

Digital signal processing for denoising electrophysiological data. - 123 p.

Adviser: Hrvoje Podnar.

Thesis (M.S.)--Southern Connecticut State University, 2008.

Neurons in the human brain exchange messages by means of electro-chemical reactions. To better understand brain functions, these messages are collected, measured and analyzed. Due to imperfect signal collection processes, the recorded signals are affected by a multitude of noise sources. In this thesis a de-noising digital signal-processing tool is developed specifically targeted to neural signals. The tool provides a user-friendly environment in which neuroscientists can easily apply a number of noise reduction algorithms tailored for data generated by neural cells. In addition, the tool provides several statistical procedures useful in analysis of neural activities.

ISBN: 9780549481553Subjects--Topical Terms:

626642
Computer Science.

Digital signal processing for denoising electrophysiological data.
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008 101007s2008 ||||||||||||||||| ||eng d
020 $a 9780549481553
035 $a (UMI)AAI1452165
035 $a AAI1452165
040 $a UMI $c UMI
100 1 $a Peng, Hui. $3 1058024
245 1 0 $a Digital signal processing for denoising electrophysiological data.
300 $a 123 p.
500 $a Adviser: Hrvoje Podnar.
500 $a Source: Masters Abstracts International, Volume: 46-05, page: 2731.
502 $a Thesis (M.S.)--Southern Connecticut State University, 2008.
520 $a Neurons in the human brain exchange messages by means of electro-chemical reactions. To better understand brain functions, these messages are collected, measured and analyzed. Due to imperfect signal collection processes, the recorded signals are affected by a multitude of noise sources. In this thesis a de-noising digital signal-processing tool is developed specifically targeted to neural signals. The tool provides a user-friendly environment in which neuroscientists can easily apply a number of noise reduction algorithms tailored for data generated by neural cells. In addition, the tool provides several statistical procedures useful in analysis of neural activities.
590 $a School code: 0928.
650 4 $a Computer Science. $3 626642
690 $a 0984
710 2 $a Southern Connecticut State University. $3 1020997
773 0 $t Masters Abstracts International $g 46-05.
790 $a 0928
790 1 0 $a Podnar, Hrvoje, $e advisor
791 $a M.S.
792 $a 2008
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1452165