Signal Processing for Neuroscientists
An Introduction to the Analysis of Physiological Signals
- 1st Edition - November 22, 2006
- Imprint: Academic Press
- Author: Wim van Drongelen
- Language: English
- Paperback ISBN:9 7 8 - 1 - 4 9 3 3 - 0 0 8 9 - 1
- eBook ISBN:9 7 8 - 0 - 0 8 - 0 4 6 7 7 5 - 7
Signal Processing for Neuroscientists introduces analysis techniques primarily aimed at neuroscientists and biomedical engineering students with a reasonable but modest backgr… Read more
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Request a sales quoteSignal 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
Neuroscientists and biomedical engineering students.
Dedication
Preface
Chapter 1: Introduction
1.1 OVERVIEW
1.2 BIOMEDICAL SIGNALS
1.3 BIOPOTENTIALS
1.4 EXAMPLES OF BIOMEDICAL SIGNALS
1.5 ANALOG-TO-DIGITAL CONVERSION
1.6 MOVING SIGNALS INTO THE MATLAB ANALYSIS ENVIRONMENT
APPENDIX 1.1
Chapter 2: Data Acquisition
2.1 RATIONALE
2.2 THE MEASUREMENT CHAIN
2.3 SAMPLING AND NYQUIST FREQUENCY IN THE FREQUENCY DOMAIN
2.4 THE MOVE TO THE DIGITAL DOMAIN
Appendix 2.1
Chapter 3: Noise
3.1 INTRODUCTION
3.2 NOISE STATISTICS
3.3 SIGNAL-TO-NOISE RATIO
3.4 NOISE SOURCES
APPENDIX 3.1
APPENDIX 3.2
APPENDIX 3.3
APPENDIX 3.4
Chapter 4: Signal Averaging
4.1 INTRODUCTION
4.2 TIME LOCKED SIGNALS
4.3 SIGNAL AVERAGING AND RANDOM NOISE
4.4 NOISE ESTIMATES AND THE ± AVERAGE
4.5 SIGNAL AVERAGING AND NONRANDOM NOISE
4.6 NOISE AS A FRIEND OF THE SIGNAL AVERAGER
4.7 EVOKED POTENTIALS
4.8 OVERVIEW OF COMMONLY APPLIED TIME DOMAIN ANALYSIS TECHNIQUES
Chapter 5: Real and Complex Fourier Series
5.1 INTRODUCTION
5.2 THE FOURIER SERIES
5.3 THE COMPLEX FOURIER SERIES
5.4 EXAMPLES
APPENDIX 5.1
APPENDIX 5.2
Chapter 6: Continuous, Discrete, and Fast Fourier Transform
6.1 INTRODUCTION
6.2 THE FOURIER TRANSFORM
6.3 DISCRETE FOURIER TRANSFORM AND THE FFT ALGORITHM
6.4 UNEVENLY SAMPLED DATA
Chapter 7: Fourier Transform Applications
7.1 SPECTRAL ANALYSIS
7.2 TOMOGRAPHY
APPENDIX 7.1
Chapter 8: LTI Systems, Convolution, Correlation, and Coherence
8.1 INTRODUCTION
8.2 LINEAR TIME INVARIANT (LTI) SYSTEM
8.3 CONVOLUTION
8.4 AUTOCORRELATION AND CROSS-CORRELATION
8.5 COHERENCE
APPENDIX 8.1
Chapter 9: Laplace and z-Transform
9.1 INTRODUCTION
9.2 THE USE OF TRANSFORMS TO SOLVE ODEs
9.3 THE LAPLACE TRANSFORM
9.4 EXAMPLES OF THE LAPLACE TRANSFORM
9.5 THE Z-TRANSFORM
9.6 THE Z-TRANSFORM AND ITS INVERSE
9.7 EXAMPLE OF THE z-TRANSFORM
APPENDIX 9.1
APPENDIX 9.2
APPENDIX 9.3
Chapter 10: Introduction to Filters: The RC Circuit
10.1 INTRODUCTION
10.2 FILTER TYPES AND THEIR FREQUENCY DOMAIN CHARACTERISTICS
10.3 RECIPE FOR AN EXPERIMENT WITH AN RC CIRCUIT
Chapter 11: Filters: Analysis
11.1 INTRODUCTION
11.2 THE RC CIRCUIT
11.3 THE EXPERIMENTAL DATA
APPENDIX 11.1
APPENDIX 11.2
APPENDIX 11.3
Chapter 12: Filters: Specification, Bode Plot, and Nyquist Plot
12.1 INTRODUCTION: FILTERS AS LINEAR TIME INVARIANT (LTI) SYSTEMS
12.2 TIME DOMAIN RESPONSE
12.3 THE FREQUENCY CHARACTERISTIC
12.4 NOISE AND THE FILTER FREQUENCY RESPONSE
Chapter 13: Filters: Digital Filters
13.1 INTRODUCTION
13.2 IIR AND FIR DIGITAL FILTERS
13.3 AR, MA, AND ARMA FILTERS
13.4 FREQUENCY CHARACTERISTIC OF DIGITAL FILTERS
13.5 MATLAB IMPLEMENTATION
13.6 FILTER TYPES
13.7 FILTER BANK
13.8 FILTERS IN THE SPATIAL DOMAIN
APPENDIX 13.1
Chapter 14: Spike Train Analysis
14.1 INTRODUCTION
14.2 POISSON PROCESSES AND POISSON DISTRIBUTIONS
14.3 ENTROPY AND INFORMATION
14.4 THE AUTOCORRELATION FUNCTION
14.5 CROSS-CORRELATION
APPENDIX 14.1
APPENDIX 14.2
Chapter 15: Wavelet Analysis: Time Domain Properties
15.1 INTRODUCTION
15.2 WAVELET TRANSFORM
15.3 OTHER WAVELET FUNCTIONS
15.4 TWO-DIMENSIONAL APPLICATION
APPENDIX 15.1
Chapter 16: Wavelet Analysis: Frequency Domain Properties
16.1 INTRODUCTION
16.2 THE CONTINUOUS WAVELET TRANSFORM (CWT)
16.3 TIME FREQUENCY RESOLUTION
16.4 MATLAB WAVELET EXAMPLES
Chapter 17: Nonlinear Techniques
17.1 INTRODUCTION
17.2 NONLINEAR DETERMINISTIC PROCESSES
17.3 LINEAR TECHNIQUES FAIL TO DESCRIBE NONLINEAR DYNAMICS
17.4 EMBEDDING
17.5 METRICS FOR CHARACTERIZING NONLINEAR PROCESSES
17.6 APPLICATION TO BRAIN ELECTRICAL ACTIVITY
References
Index
- Edition: 1
- Published: November 22, 2006
- No. of pages (eBook): 320
- Imprint: Academic Press
- Language: English
- Paperback ISBN: 9781493300891
- eBook ISBN: 9780080467757
Wv
Wim van Drongelen
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/
Affiliations and expertise
Department of Pediatrics, University of Chicago, Chicago, IL, USARead Signal Processing for Neuroscientists on ScienceDirect