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

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