Signal Processing for Neuroscientists: An Introduction to the Analysis of Physiological Signals
Signal Processing for Neuroscientists: An Introduction to the Analysis of Physiological Signals Books
Product 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, unity, 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 matter-of-fact 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 know the principles of commercially available analyses software, and to allow him/her to hypothesis 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, blast characteristics, and recording techniques
· Basics and background for more advanced topics can be found in extensive notes and appendices
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This book is clearly not proposed for the beginner. It is proposed for graduate students or undergraduates with a excellent working knowledge of at least calculus although many people benefit from previous exposure to differential equations in reading this book. There are many books out there in the math and physics literature that cover many of these topics but are entirely incomprehensible to the average neuroscientist. This book is the only book on the market that bridges the knowledge gap between students who already possess an introductory quantitative background and those capable of reading modern quantitative literature from fields such as engineering and signal processing. It is also the only book for neuroscientists that introduces these more advanced concepts from the perspective of a neuroscience (i.e. using EEG recordings, etc. to illustrate the methodology). Finally, the Matlab code presented in the book can in many instances be used directly in one’s own research making this book a very matter-of-fact investment.
Rating: 5 / 5
As a new user to Matlab, I found this book too challenging to be effective.
Rating: 3 / 5
This book contains helpful exercises and demonstrations of MATLAB code that are worth looking at. Overall, I reckon it covers the major topics and does a clad job fulfilling that purpose.
Having said that, but, the language of the book is not reader-friendly. It’s not to say that we aren’t dealing with advanced material here, because it wasn’t proposed for the beginner. Don’t guess that you’ll just be able to pick up the text and read it without any prior knowledge.
I would have given this book an additional star, but, there are some errors of calculation in the beginning exercises. If you are the advanced reader, you’ll pick up on these–someone other than myself really picked up on these, so don’t just take the calculation and their end result to be the resolution–as everlastingly, be cautious when you read.
Rating: 4 / 5