Paper available: "The Dependence Identification Neural Network Construction Algorithm

[Panos Antsaklis]

FTP-host: rottweiler.ee.nd.edu
FTP-filename: /pub/isis/tnn1845.ps.gz

The following paper is available by anonymous ftp.  It will appear in an
upcoming issue of the IEEE Transactions on Neural Networks.

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    THE DEPENDENCE IDENTIFICATION NEURAL NETWORK CONSTRUCTION ALGORITHM

                  John O. Moody and  Panos J. Antsaklis


                      Dept. of Electrical Engineering
                      University of Notre Dame
                      Notre Dame, IN 46556, USA
                      email: jmoody at maddog.ee.nd.edu


     (Accepted for publication in the IEEE Transactions on Neural Networks)



                               Abstract

	An algorithm for constructing and training multilayer neural networks,
dependence identification, is presented in this paper.  Its distinctive
features are that (i) it transforms the training problem into a set of
quadratic optimization problems that are solved by a number of linear
equations, (ii) it constructs an appropriate network to meet the training
specifications, and (iii) the resulting network architecture and weights can be
further refined with standard training algorithms, like backpropagation, giving
a significant speed-up in the development time of the neural network and
decreasing the amount of trial and error usually associated with network
development.


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ftp instructions:

unix% ftp rottweiler.ee.nd.edu
Name: anonymous
password: your email address
ftp> cd pub/isis
ftp> binary
ftp> get tnn1845.ps.gz
ftp> bye
unix% gzip -d tnn1845.ps.gz
unix% lpr tnn1845.ps

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