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Digital signal processing for denois...

Southern Connecticut State University.

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Digital signal processing for denoising electrophysiological data.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Digital signal processing for denoising electrophysiological data./
作者:	Peng, Hui.
面頁冊數:	123 p.
附註:	Adviser: Hrvoje Podnar.
Contained By:	Masters Abstracts International46-05.
標題:	Computer Science. -
電子資源:	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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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.
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