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Table of contents
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1 - Introduction
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2 - Data Acquisition
Pages 15-33 - Book chapterNo access
3 - Noise
Pages 35-53 - Book chapterNo access
4 - Signal Averaging
Pages 55-70 - Book chapterNo access
5 - Real and Complex Fourier Series
Pages 71-90 - Book chapterNo access
6 - Continuous, Discrete, and Fast Fourier Transform
Pages 91-105 - Book chapterNo access
7 - Fourier Transform Applications
Pages 107-126 - Book chapterNo access
8 - LTI Systems, Convolution, Correlation, and Coherence
Pages 127-149 - Book chapterNo access
9 - Laplace and z-Transform
Pages 151-168 - Book chapterNo access
10 - Introduction to Filters: The RC Circuit
Pages 169-175 - Book chapterNo access
11 - Filters: Analysis
Pages 177-188 - Book chapterNo access
12 - Filters: Specification, Bode Plot, and Nyquist Plot
Pages 189-203 - Book chapterNo access
13 - Filters: Digital Filters
Pages 205-217 - Book chapterNo access
14 - Spike Train Analysis
Pages 219-243 - Book chapterNo access
15 - Wavelet Analysis: Time Domain Properties
Pages 245-263 - Book chapterNo access
16 - Wavelet Analysis: Frequency Domain Properties
Pages 265-277 - Book chapterNo access
17 - Nonlinear Techniques
Pages 279-295 - Book chapterNo access
References
Pages 297-300 - Book chapterNo access
Index
Pages 301-308
About the book
Description
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®.
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®.
Key Features
- 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
- 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
Details
ISBN
978-0-12-370867-0
Language
English
Published
2007
Copyright
Copyright © 2007 Elsevier Inc. All rights reserved
Imprint
Academic Press