Method matrix/linlsqsvd


  LINLSQSVD Linear least squares with singular value decomposition
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  DESCRIPTION: Linear least square problem with singular value
  decomposition
 
  ALGORITHM: % It solves the problem
 
         Y = HX
 
  where X are the parameters, Y the measurements, and H the linear
  equations relating the two.
  It is able to perform linear identification of the parameters of a
  multichannel systems. The results of different experiments on the same
  system can be passed as input. The algorithm, thanks to the singular
  value decomposition, extract the maximum amount of information from each
  single channel and for each experiment. Total information is then
  combined to get the final result.
             
  CALL:                   pars = linfitsvd(H1,...,HN,Y,pl);
  
  If the experiment is 1 then H1,...,HN and Y are aos.
  If the experiments are M, then H1,...,HN and Y are Mx1 matrix objects
  with the aos relating to the given experiment in the proper position.
  
  INPUT:
                - Hi represent the columns of H
                - Y represent the measurement set
  
  OUTPUT:
                - pars: a pest object containing parameter estimation
  
  09-11-2010 L Ferraioli
        CREATION
 
  Parameters Description
 
  VERSION:     $Id: linlsqsvd.m,v 1.9 2011/05/02 14:18:19 luigi Exp $
 
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Method Details
Access public
Defining Class matrix
Sealed 0
Static 0

Parameter Description

Default

no description
Key Default Value Options Description
KNOWNPARAMS {} [0x0] none Known Parameters. A struct array with the fields:
  • pos - a number indicating the corresponding position of the parameter (corresponding column of H)
  • value - the value for the parameter
  • err - the uncertainty associated to the parameter
STHRESHOLD [] none Fix upper treshold for singular values.Singular values larger than the value will be ignored.This correspon to consider only parameters combinations with error lower then the value
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Some information of the method ao/linlsqsvd are listed below:
Class name ao
Method name linlsqsvd
Category Signal Processing
CVS Version $Id: linlsqsvd.m,v 1.9 2011/05/02 14:18:19 luigi Exp $
Min input args 2
Max input args -1
Min output args 1
Max output args -1




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