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El. knyga: Signal Processing for Neuroscientists: An Introduction to the Analysis of Physiological Signals

3.82/5 (34 ratings by Goodreads)
(Department of Pediatrics, University of Chicago, Chicago, IL, USA)
  • Formatas: PDF+DRM
  • Išleidimo metai: 18-Dec-2006
  • Leidėjas: Academic Press Inc
  • Kalba: eng
  • ISBN-13: 9780080467757
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  • Formatas: PDF+DRM
  • Išleidimo metai: 18-Dec-2006
  • Leidėjas: Academic Press Inc
  • Kalba: eng
  • ISBN-13: 9780080467757
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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
* A Companion Website hosts the MATLAB scripts and several data files:
   http://www.elsevierdirect.com/companion.jsp ISBN=9780123708670

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
* A Companion Website hosts the MATLAB scripts and several data files:
http://www.elsevierdirect.com/companion.jsp ISBN=9780123708670

Daugiau informacijos

An introduction to signal analysis ranging from data acquisition to data processing; and from the mathematical background of the analysis to the practical application of processing algorithms.
1 Introduction
1
2 Data Acquisition
15
3 Noise
35
4 Signal Averaging
55
5 Real and Complex Fourier Series
71
6 Continuous, Discrete, and Fast Fourier Transform
91
7 Fourier Transform Applications
107
8 LTI Systems, Convolution, Correlation, and Coherence
127
9 Laplace and z-Transform
151
10 Introduction to Filters: the RC Circuit 169
11 Filters: Analysis 177
12 Filters: Specification, Bode Plot, and Nyquist Plot 189
13 Filters: Digital Filters 205
14 Spike Train Analysis 219
15 Wavelet Analysis: Time Domain Properties 245
16 Wavelet Analysis: Frequency Domain Properties 265
17 Nonlinear Techniques 279
References 297
Index 301
Wim van Drongelen studied Biophysics at the University Leiden, The Netherlands. After a period in the Laboratoire d'Electrophysiologie, Université Claude Bernard, Lyon, France, he received the Doctoral degree cum laude. In 1980 he received the Ph.D. degree. He worked for the Netherlands Organization for the Advancement of Pure Research (ZWO) in the Department of Animal Physiology, Wageningen, The Netherlands. He lectured and founded a Medical Technology Department at the HBO Institute Twente, The Netherlands. In 1986 he joined the Benelux office of Nicolet Biomedical as an Application Specialist and in 1993 he relocated to Madison, WI, USA where he was involved in research and development of equipment for clinical neurophysiology and neuromonitoring. In 2001 he joined the Epilepsy Center at The University of Chicago, Chicago, IL, USA. Currently he is Professor of Pediatrics, Neurology, and Computational Neuroscience. In addition to his faculty position he serves as Technical and Research Director of the Pediatric Epilepsy Center and he is Senior Fellow with the Computation Institute. Since 2003 he teaches applied mathematics courses for the Committee on Computational Neuroscience. His ongoing research interests include the application of signal processing and modeling techniques to help resolve problems in neurophysiology and neuropathology. For details of recent work see http://epilepsylab.uchicago.edu/