no subject (file transmission)

[Benny Lautrup]

Subject: Paper available: Extremely Ill-posed Learning
Date: August 29, 1994

FTP-host: connect.nbi.dk
FTP-file: neuroprose/hansen.ill-posed.ps.Z

----------------------------------------------

The following paper is now available:

Extremely Ill-posed Learning [14 pages]

L.K. Hansen, B. Lautrup, I. Law, N. Moerch, and J. Thomsen
CONNECT, The Niels Bohr Institute, University of Copenhagen, Denmark
 
Abstract:
Extremely ill-posed learning problems  are  common  in  image  and
spectral analysis. They are characterized  by  a  vast  number  of
highly correlated inputs, eg pixel  or  or  pin  values,  and  a
modest number of patterns, eg images or spectra. We show that it
is possible to  train  neural  networks  to  learn  such  patterns
without using an excessive number of weights, and we devise a test
to decide if new patterns should be included in the  training  set
or whether they fall within the  subspace  already  explored.  The
method is applied to the analysis of PET-images.

Please do not reply directly to this message.

-----------------------------------------------

FTP-instructions:

unix> ftp connect.nbi.dk (or 130.225.212.30)
ftp> Name: anonymous
ftp> Password: your e-mail address
ftp> cd neuroprose
ftp> binary
ftp> get hansen.ill-posed.ps.Z
ftp> quit
unix> uncompress hansen.ill-posed.ps.Z
        
-----------------------------------------------

Benny Lautrup,
Computational Neural Network Center (CONNECT)
Niels Bohr Institute
Blegdamsvej 17
2100 Copenhagen
Denmark

Telephone: +45-3532-5200
Direct:    +45-3532-5358
Fax:       +45-3142-1016
e-mail:    lautrup at connect.nbi.dk