|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
PRACTICAL NETWORK DESIGN AND IMPLEMENTATION
The aim of this paper is to put Artificial Neural Network techniques in perspective, discussing the practical issues of network design and implementation. Firstly, a comparison is made with other pattern matching techniques with an overview of the capabilities and complexity of these techniques. Some basic ground in multi-layer perceptrons is then covered so that a link may be made between these and Gaussian classifiers. In the process, some of the practical difficulties associated with gradient descent based training are covered, along with the popular remedies. Finally, the paper is concluded with a summary of the advantages of recurrent networks and a review of the architectures available.
If you have difficulty viewing files that end
which are gzip compressed, then you may be able to find
tools to uncompress them at the gzip
If you have difficulty viewing files that are in PostScript, (ending
'.ps.gz'), then you may be able to
find tools to view them at
We have attempted to provide automatically generated PDF copies of documents for which only PostScript versions have previously been available. These are clearly marked in the database - due to the nature of the automatic conversion process, they are likely to be badly aliased when viewed at default resolution on screen by acroread.
|| Search | CUED | Cambridge University ||
2005 Cambridge University Engineering Dept
Information provided by milab-maintainer