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Contents
Contents
An introduction to the treatment of neurophysiological signals using Scilab
Jesus Olivan Palacios
version 0.02, may 2001
Contents
Introduction
Some general features about Scilab
Matrices as physiological traces
Matrices in Scilab
Sampling a signal
Access to the components of a vector
Access to the components of a vector: an example
Plotting a vector or some part of a vector. Use of several windows
Operating with arrays as a whole. Averaging
Global operation on vectors
Measuring curves
Averaging curves
Programming Scilab
`Sce' files
Inline functions
`Sci' files
Programming in Fortran or C
Input and output of programs, conditionals and loops, vectorial commands, and lists
Files: reading and writing data
Scilab variables
ASCII files
Binary files
wav files
A format used in Clinical Neurophysiology: EDF
Data in Clinical Neurophysiology.
Array of indexes as a label by which we can mark long signals
Some general concepts of signal treatment applied to Clinical Neurophysiology
Convolution
Introduction
Mechanics of convolution
Convolution and product of polynomials
Filtering with convolution
Synthesis of signals with convolution
In summary
Correlation
Introduction to correlation
Correlation of noise
Autocorrelation of a noised signal
Mechanics of correlation
Correlation as a tool to align signals
Correlation used to extract transients from a signal
In summary
Filters
Introduction
Filtering sinusoids
Properties of the filter
Filtering neurophysiological signals
Correcting distortions
Other ways of filtering: FIR filtering
In summary
Fourier Transform
Introduction
Windowing
Power Spectrum
Some commands used to calculate the module of complex values in Scilab
Power Spectrum of a sinusoid
Power Spectrum of a noised sinusoid
Power Spectrum of an ECG signal
Power spectrum of white noise and filtered noise
Spectrogram
Coherence
In summary
About this document ...
je 2006-10-13
