Paper available in Neuroprose

[Hong Chen]

Ftp-Host: archive.cis.ohio-state.edu
Ftp-Filename: /pub/neuroprose/chen.function_approx.ps.Z


The following paper chen.function_approx.ps.Z (15 pages) is now
available via anonymous ftp from the neuroprose archive.  It has been
accepted by IEEE Transactions on Neural Networks.

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         Approximation Capability in C(R^n) by Multilayer 
            Feedforward Networks and Related Problems


                         Tianping Chen
                    Department of Mathematics
                        Fudan University
                      Shanghai, P.R. China


                           Hong Chen
                     VLSI Libraries, Inc.
                       3135 Kifer Road
                     Santa Clara, CA 95052
                             USA


                         Ruey-wen Liu
               Department of Electrical Engineering
                    University of Notre Dame
                      Notre Dame, IN 46556
                             USA
                    

ABSTRACT:	 In this paper, we investigate the capability of
approximating functions in C(R^n) by three-layered neural networks
with sigmoidal function in the hidden layer.  It is found that the
boundedness condition on the sigmoidal function plays an essential
role in the approximation, in contrast to continuity or monotonity
condition.  We point out that in order to prove the neural network
approximation capability in the n-dimensional case, all one needs to
do is to prove the case for one dimension.  The approximation in
L^p-norm and some related problems are also discussed.

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             Instruction for retrieving this paper:

unix% ftp archive.cis.ohio-state.edu

ftp-login: anonymous
ftp-password: <your email address>

ftp> cd pub/neuroprose
ftp> binary
ftp> get chen.function_approx.ps.Z
ftp> bye

unix% uncompress chen.function_approx.ps.Z

unix% lpr chen.function_approx.ps    (or however you print postscript)