
dminorm(1)                   Khoros                    dminorm(1)

PROGRAM
     dminorm - 1D Minimum-Norm Spectral Estimation

SYNTAX
     dminorm

     -i             input file (xviff file)

     -o             resulting output file (xviff file)

     [-s]           model order (same as number of eigenvectors)

     [-f]           specify number of spectral values desired

     [-p]           do not center the result (0) or center the
                    result (1)

     [-j]           use scalar (0) or vector (1) processing on
                    complex data

     [-d]           data processing direction (0 = down vectors,
                    1 = across bands)

     [-g]           type of autocorrelation file to be used:
                    0 (choose biased autocorrelation estimate),
                    1 (choose unbiased autocorrelation estimate),
                    or 2 (choose FFT based autocorrelation esti-
                    mate)
                       [default = 0]

     [-c]           Use AIC (0) or MDL(1) criterion
                                        -OR-

     [-k]           dimension of noise subspace sequence

     [-V]           Gives the version for dminorm

     [-U]           Gives the usage for dminorm

     [-P]           Prompts for command line options

     [-A [file1]]   Creates the answer file called dminorm.ans or
                    file1

     [-a [file1]]   Uses dminorm.ans or file1 as the answer file

DESCRIPTION
     An implementation of the Minimum Norm for spectral estima-
     tion.  Minimum Norm is a spectral estimation technique based
     on eigendecomposition of the autocorrelation matrix of a
     sampled random process.  The Minimum Norm algorithm attempts
     to eliminate the effects of spurious zeros, which result in
     spurious peaks in the power spectrum, by pushing them inside
     the unit circle.

     The algorithm involves generating estimates of the eigen-
     values and eigenvectors of a Toelitz and Hermitian auto-
     correlation matrix estimate.  The eigenvectors are then
     sorted by ascending order of their corresponding eigen-
     values.  The eigenvectors corresponding to the k smallest,
     approximately equal eigenvalues are selected.  k is the
     dimension of the noise subspace, and can be specified by the
     user or may be computed using the Akaike (AIC) or Minimum
     Description Length (MDL) information theoretic criteria.

     The Minimum Norm power spectrum is computed by solving an
     ordinary linear prediction problem.

     For a more theoretical discussion of the Minimum Norm algo-
     rithm see:  Optimum Signal Processing by Sophocles
     Orfranidis, McGraw-Hill, 1988; or Eigenvector-Based
     Parametric Modeling of Time-Domain Signals:  Application to
     Nuclear Magnetic Resonance Spectroscopy by Glen Abousleman
     (Master's thesis, University of New Mexico, Dept. of EECE,
     1990).

     dminorm does not work on explicit location data and will
     return an error when such a file is encountered.  No output
     file will be created.  dminorm works only on VFF_TYP_FLOAT
     or VFF_TYP_COMPLEX data files.

     Input/Output Files
     The input file must be of type VFF_TYP_FLOAT or
     VFF_TYP_COMPLEX.  The output file returned will be of size
     specified by the user.  If the data is of type
     VFF_TYP_COMPLEX and complex aithmetic is selected then the
     output file will be of type VFF_TYP_FLOAT.
     *********************************************************************

     Process direction
     Data can be processed with either band or vector orientation
     (-d option).  The default data processing direction is in
     the vector direction (-d = 0).  pixel location.  The direc-
     tion of processing can be changed so that each band is pro-
     cessed as a signal (instead of each vector being a signal)
     by setting the -d option to 1.

REQUIRED ARGUMENTS
     -i     type: infile
            desc: input file (xviff file)

     -o     type: outfile
            desc: resulting output file (xviff file)

OPTIONAL ARGUMENTS
     -s     type: integer
            desc: model order (same as number of eigenvectors)
            default: 1
            bounds: value > 0

     -f     type: integer
            desc: specify number of spectral values desired
            default: 1
            bounds: value > 0

     -p     type: boolean
            desc: do not center the result (0) or center the
            result (1)
            default: false

     -j     type: boolean
            desc: use scalar (0) or vector (1) processing on com-
            plex data
            default: true

     -d     type: boolean
            desc: data processing direction (0 = down vectors, 1
            = across bands)
            default: true

     -g     type: integer
            desc: type of autocorrelation file to be used
            allowed values:
            0 (choose biased autocorrelation estimate),
            1 (choose unbiased autocorrelation estimate),
            or 2 (choose FFT based autocorrelation estimate)

     ***   These arguments are MUTUALLY EXCLUSIVE   ***
      If desired, you may provide ONE AND ONLY ONE of:

     -c     desc: Use AIC (0) or MDL(1) criterion
            default: false

     -k     desc: dimension of noise subspace sequence
            default: 1
            bounds: value >= 0

            ********

EXAMPLES
SEE ALSO
     intro(1), verror(3), vgparms(3), vutils(3), ldminorm(3)

RESTRICTIONS
     works only on VFF_TYP_COMPLEX and VFF_TYP_FLOAT.

     dminorm does not work on explicit location data and will
     return an error when such a data file is encountered.

COPYRIGHT
     Copyright 1992, University of New Mexico.  All rights
     reserved.

Khoros                    Release: 1.0                          1

