Signal Processing for Neuroscientists
- 13 %

Signal Processing for Neuroscientists

An Introduction to the Analysis of Physiological Signals
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Wim van Drongelen
645 g
236x158x22 mm

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:
Chapter 1: Introduction

Chapter 2: Data Acquisition

Chapter 3: Noise

Chapter 4: Signal Averaging

Chapter 5: Real and Complex Fourier Series

Chapter 6: Continuous, Discrete, and Fast Fourier Transform

Chapter 7: Fourier Transform Applications

Chapter 8: LTI Systems, Convolution, Correlation, and Coherence

Chapter 9: Laplace and z-Transform

Chapter 10: Introduction to Filters: The RC Circuit

Chapter 11: Filters: Analysis

Chapter 12: Filters: Specification, Bode Plot, and Nyquist Plot

Chapter 13: Filters: Digital Filters

Chapter 14: Spike Train Analysis

Chapter 15: Wavelet Analysis: Time Domain Properties

Chapter 16: Wavelet Analysis: Frequency Domain Properties

Chapter 17: Nonlinear Techniques



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