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Signal processing for neuroscientists[electronic resource] :introduction to the analysis of physiological signals /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	612.8
書名/作者:	Signal processing for neuroscientists : introduction to the analysis of physiological signals // Wim van Drongelen.
作者:	Drongelen, Wim van.
出版者:	Burlington, Mass. : : Academic Press,, c2007.
面頁冊數:	ix, 308 p. : : col. ill. ;; 24 cm. + + 1 CD-ROM (4 3/4 in.)
標題:	Signal processing - Digital techniques.
標題:	Neurosciences - Data processing.
標題:	Neurology - Mathematical models.
標題:	Physiology - Mathematical models.
ISBN:	9780123708670
ISBN:	0123708672
書目註:	Includes bibliographical references (p. 297-300) and index.
內容註:	Introduction -- Data Acquisition -- Noise -- Signal Averaging -- Real and Complex Fourier Series -- Continuous, Discrete, and Fast Fourier Transform -- Fourier Transform Applications -- LTI systems, Convolution, Correlation, and Coherence -- Laplace and z-Transform -- Introduction to Filters: the RC-Circuit -- Filters: Analysis -- Filters: Specification, Bode plot, Nyquist plot -- Filters: Digital Filters -- Spike Train Analysis -- Wavelet Analysis: Time Domain Properties -- Wavelet Analysis: Frequency Domain Properties -- Nonlinear Techniques.
摘要、提要註:	Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the golden trio in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB�. Multiple color illustrations are integrated in the text Includes an introduction to biomedical signals, noise characteristics, and recording techniques Basics and background for more advanced topics can be found in extensive notes and appendices.
電子資源:	An electronic book accessible through the World Wide Web; click for information

Signal processing for neuroscientists[electronic resource] :introduction to the analysis of physiological signals /
Drongelen, Wim van.

Signal processing for neuroscientistsintroduction to the analysis of physiological signals /[electronic resource] :Wim van Drongelen. - Burlington, Mass. :Academic Press,c2007. - ix, 308 p. :col. ill. ;24 cm. +1 CD-ROM (4 3/4 in.)

Includes bibliographical references (p. 297-300) and index.

Introduction -- Data Acquisition -- Noise -- Signal Averaging -- Real and Complex Fourier Series -- Continuous, Discrete, and Fast Fourier Transform -- Fourier Transform Applications -- LTI systems, Convolution, Correlation, and Coherence -- Laplace and z-Transform -- Introduction to Filters: the RC-Circuit -- Filters: Analysis -- Filters: Specification, Bode plot, Nyquist plot -- Filters: Digital Filters -- Spike Train Analysis -- Wavelet Analysis: Time Domain Properties -- Wavelet Analysis: Frequency Domain Properties -- Nonlinear Techniques.

Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest background in mathematics, physics, and computer programming. The focus of this text is on what can be considered the golden trio in the signal processing field: averaging, Fourier analysis, and filtering. Techniques such as convolution, correlation, coherence, and wavelet analysis are considered in the context of time and frequency domain analysis. The whole spectrum of signal analysis is covered, ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms. Overall, the approach to the mathematics is informal with a focus on basic understanding of the methods and their interrelationships rather than detailed proofs or derivations. One of the principle goals is to provide the reader with the background required to understand the principles of commercially available analyses software, and to allow him/her to construct his/her own analysis tools in an environment such as MATLAB�. Multiple color illustrations are integrated in the text Includes an introduction to biomedical signals, noise characteristics, and recording techniques Basics and background for more advanced topics can be found in extensive notes and appendices.

Electronic reproduction.
Amsterdam :
Elsevier Science & Technology,
2007.

Mode of access: World Wide Web.

ISBN: 9780123708670

Source: 131925:132032Elsevier Science & Technologyhttp://www.sciencedirect.comSubjects--Topical Terms:

405038
Signal processing
--Digital techniques.Index Terms--Genre/Form:

336502
Electronic books.

LC Class. No.: RC343 / .D76 2007eb

Dewey Class. No.: 612.8

Signal processing for neuroscientists[electronic resource] :introduction to the analysis of physiological signals /
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