Line filter: Difference between revisions
Jump to navigation
Jump to search
imported>Neal |
imported>Neal (→Inputs) |
||
Line 18: | Line 18: | ||
:::'box', (win) is the half-width in number of channels. | :::'box', (win) is the half-width in number of channels. | ||
:::'triangular', (win) is the half-width in channels. | :::'triangular', (win) is the half-width in channels. | ||
:2) If (win) is 1xN, then it is used as the PSF and (options.psf) is ignored. | :2) If (win) is 1xN vector, then it is used as the PSF and (options.psf) is ignored. The FFT of the PSF is calculated and used in the convolution or deconvolution algorithm. | ||
====Outputs==== | ====Outputs==== |
Revision as of 09:08, 17 March 2009
Purpose
Spectral filtering spectral filtering via convolution and deconvolution.
Synopsis
- xf = line_filter(x,win,options);
Description
Inputs
- x = MxN matrix of data of class 'double' or 'dataset'. If 'dataset' it must x.type=='data'. Each of the M rows are convolved with the linear filter given in (options.lineshape).
- win =
- 1) A scalar parameter corresponding to the analogous window width of the filter.
- options.psf =
- 'gaussian', (win) corresponds to the std in the Gaussian distribution.
- 'box', (win) is the half-width in number of channels.
- 'triangular', (win) is the half-width in channels.
- options.psf =
- 2) If (win) is 1xN vector, then it is used as the PSF and (options.psf) is ignored. The FFT of the PSF is calculated and used in the convolution or deconvolution algorithm.
Outputs
- xf = Filtered data of class 'dataset'.
Options
options = a structure array with the following fields:
- psf: [ {'gaussian'} | 'box' | 'triangular'] Line shape or point source function (PSF) for filtering.