Method ao/crb


  CRB computes the inverse of the Fisher Matrix
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  DESCRIPTION: CRB computes the inverse of the Fisher Matrix
 
  CALL:        bs = crb(in,pl)
 
  INPUTS:      in      - matrix objects with input signals to the system
               model   - symbolic models containing the transfer function model
 
               pl      - parameter list
 
  OUTPUTS:     bs   - covariance matrix AO
 
  Parameters Description
 
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Method Details
Access public
Defining Class ao
Sealed 0
Static 0

Parameter Description

Default

no description
Key Default Value Options Description
NAVS 5 none The number of averages to use when calculating PSD and CPSD.
FITPARAMS '' none Parameters of the model
INNAMES 1 none Input names. Used for ssm models.
OUTNAMES 1 none Output names. Used for ssm models.
PARAMSVALUES 1 none The numerical values of the parameters.
MODEL '' none An array of matrix models
INPUT '' none The input signal to the system. It should be a matrix of AOs, the rows denoting the channels, and the columns the number of experiments. An array of matrix objects is also accepted.
PINV 1
  • 1
  • 0
Use the Penrose-Moore pseudoinverse
TOL [] none Tolerance for the Penrose-Moore pseudoinverse
DIFFSTEP [] none Numerical differentiation step for ssm models
NGRID [] none Number of points in the grid to compute the optimal differentiation step for ssm models
STEPRANGES [] none An array with upper and lower values for the parameters ranges. To be used to compute the optimal differentiation step for ssm models.
LOG PARAMETERS [] none An array with upper and lower values for the parameters ranges. To be used to compute the optimal differentiation step for ssm models.
FREQUENCIES [] none The frequencies to perform the analysis.
FSOUT [] none Resampling.
F1 [] none Initial frequency for the analysis.
F2 [] none Final frequency for the analysis.
NOISE SCALE 'PSD'
  • 'PSD'
  • 'LPSD'
Select the way to handle the noise/weight data. Can use the PSD/CPSD or the LPSD/CLPSD functions.
NFFT -1 none The number of samples in each fft [default: length of input data].
A string value containing the variable 'fs' can also be used, e.g.,
plist('Nfft', '2*fs')
WIN 'Hanning'
  • 'Rectangular'
  • 'Welch'
  • 'Bartlett'
  • 'Hanning'
  • 'Hamming'
  • 'Nuttall3'
  • 'Nuttall4'
  • 'Nuttall3a'
  • 'Nuttall3b'
  • 'Nuttall4a'
  • 'Nuttall4b'
  • 'Nuttall4c'
  • 'BH92'
  • 'SFT3F'
  • 'SFT3M'
  • 'FTNI'
  • 'SFT4F'
  • 'SFT5F'
  • 'SFT4M'
  • 'FTHP'
  • 'HFT70'
  • 'FTSRS'
  • 'SFT5M'
  • 'HFT90D'
  • 'HFT95'
  • 'HFT116D'
  • 'HFT144D'
  • 'HFT169D'
  • 'HFT196D'
  • 'HFT223D'
  • 'HFT248D'
  • 'Kaiser'
  • 'levelledHanning'
The window to be applied to the data to remove the discontinuities at edges of segments. [default: taken from user prefs]
Only the design parameters of the window object are used. Enter a string value containing the window name e.g.
plist('Win', 'Kaiser', 'psll', 200)
plist('Win', 'BH92')
PSLL 200 none The peak sidelobe level for Kaiser windows.
Note: it is ignored for all other windows
OLAP -1 none The segment percent overlap [-1 == take from window function]
ORDER, N 0
  • -1
  • 0
  • 1
  • 2
  • 3
  • 4
  • 5
  • 6
  • 7
  • 8
  • 9
The order of segment detrending:
  • -1 - no detrending
  • 0 - subtract mean
  • 1 - subtract linear fit
  • N - subtract fit of polynomial, order N
TIMES, SPLIT [] none The time range to analyze. If not empty, sets the time interval to operate on.
As in ao/split, the interval can be specified by:
  • a vector of doubles
  • a timespan object
  • a cell array of time strings
  • a vector of time objects
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Some information of the method ao/crb are listed below:
Class name ao
Method name crb
Category Signal Processing
Package name ltpda
VCS Version 8ab8cbbc4bccf7543491a24448f4aae0b1be1c43
Min input args 1
Max input args -1
Min output args 1
Max output args -1




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