Signal and Image Processing Toolbox for Analyzing Intracranial Electroencephalography Data
Implicitly smooth a triangular mesh
Simple 3-dimensional sphere mesh
Sub-divide (up-sample) a triangular mesh
Subset mesh by vertex
Sample a surface mesh uniformly
Update vertex normal
'Morlet' wavelet transform (Discrete)
Band-pass signals
Calculate Contrasts of Arrays in Different Methods
'Butterworth' filter with maximum order
Check 'Arma' filter
A naive implementation of non-negative matrix factorization
Create a Matrix4 instance for 'Affine' transform
Create a Quaternion instance to store '3D' rotation
Create a Vector3 instance to store '3D' points
Apply 'Notch' filter
Set or get thread options
Create a two-dimensional plane in three dimensional space
Plot one or more signal traces in the same figure
Project plane to a surface
Calculate 'Welch Periodogram'
Convert raw vectors to R vectors
Computer reciprocal condition number of an 'Arma' filter
Objects exported from other packages
Find and interpolate stimulation pulses
Create surface mesh from 3D-array
Find nearest k points
Compute volume for manifold meshes
Cast rays to intersect with mesh
Remove the trend for one or more signals
Least-squares linear-phase FIR filter design
Frequency response of digital filter
Collapse array
Convolution of 1D, 2D, 3D data via FFT
Decimate with 'FIR' or 'IIR' filter
Design 'FIR' filter using firls
Design an 'IIR' filter
Design a digital filter
Show channel signals with diagnostic plots
Diagnose digital filter
Calculate distances along a surface
Calculate massive covariance matrix in parallel
Compute quantiles
Fill a volume cube based on water-tight surface
Filter one-dimensional signal
Filter window functions
Forward and reverse filter a one-dimensional signal
Find peaks of a signal
Window-based FIR filter design
Apply gamma-tone filters to obtain auditory envelopes
Grow volume mask
Get external function from 'RAVE'
Internal function
'Matlab' heat-map plot palette
Generate 3D mesh surface from volume data
Compute 'multitaper' spectral densities of time-series data
Imaging registration using 'NiftyReg'
Sample '3D' volume in the world (anatomical 'RAS') space
Safe ways to call package 'rgl' without requiring 'x11'
Shift array by index
Implemented fast and memory-efficient Notch-filter, Welch-periodogram, discrete wavelet spectrogram for minutes of high-resolution signals, fast 3D convolution, image registration, 3D mesh manipulation; providing fundamental toolbox for intracranial Electroencephalography (iEEG) pipelines. Documentation and examples about 'RAVE' project are provided at <https://rave.wiki>, and the paper by John F. Magnotti, Zhengjia Wang, Michael S. Beauchamp (2020) <doi:10.1016/j.neuroimage.2020.117341>; see 'citation("ravetools")' for details.
Useful links