Summary
- Plugin name : AutoRegressive Coefficients
- Version : 1.0
- Author : Alison Cellard
- Company : Inria
- Short description : Estimates autoregressive (AR) coefficients from a set of signals
- Documentation template generation date : Oct 29 2020
Description
Estimates autoregressive (AR) linear model coefficients using Burg's method
The AR features box calculate the coefficients using Burg's method [1] to compute the AutoRegressive (AR) model of an input signal. The AR model is a representation that describes a time varying process by its own previous values.
The definition used is :
Where a(i) are the autoregressive coefficients or parameters of the model, x(t) is the input signal, x(t-i) its previous values, N is the order (length) of the model and epsilon(t) is the residue, assumed to be Gaussian white noise.
For more informations about AR model :
https://en.wikipedia.org/wiki/Autoregressive_model
http://paulbourke.net/miscellaneous/ar/
The model order (see [2]) needs to be specified in the settings of the box.
[1] Burg, J.P. (1967) "Maximum Entropy Spectral Analysis", Proceedings of the 37th Meeting of the Society of Exploration Geophysicists, Oklahoma City, Oklahoma
[2] D.J. Krusienski, D.J. MacFarland, J.R. Wolpaw. An evaluation of autoregressive spectral estimation model order for brain-computer interface application. Proceedings of the 28th IEEE EMBS Annual International Conference, New York City, USA, Aug 30-Sept 3, 2006
Inputs
1. EEG Signal
The input signal
- Type identifier : Signal (0x5ba36127, 0x195feae1)
Outputs
1. AR Features
The AR coefficients stored in a Feature vector
- Type identifier : Streamed matrix (0x544a003e, 0x6dcba5f6)
Settings
1. Order
Specify the order, thus the number of coefficients calculated
- Type identifier : Integer (0x007deef9, 0x2f3e95c6)
- Default value : [ 1 ]
Examples
Miscellaneous
The output feature vector contains the coefficients for each channel : the first [order+1] elements are the coefficients of the first channel, etc.
Generated on Tue Jun 26 2012 15:25:54 for Documentation by 1.7.4