Vasconcelos, G.C. and Fairhurst, M.C. and Bisset, D.L. (1995) INVESTIGATING FEEDFORWARD NEURAL NETWORKS WITH RESPECT TO THE REJECTION OF SPURIOUS PATTERNS. Pattern Recognition Letters, 16 (2). pp. 207-212. ISSN 0167-8655.
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The reliability of feedforward neural networks with respect to the rejection of patterns not belonging to the defined training classes is investigated. It is shown how networks with different activation functions and propagation rules construct the decision regions in the pattern space and, therefore, affect the network's performance in dealing with spurious information. A modification to the standard MLP structure is described to enhance its reliability in this respect.
|Uncontrolled keywords:||FEEDFORWARD NEURAL NETWORKS; PATTERN CLASSIFICATION|
|Subjects:||Q Science > QA Mathematics (inc Computing science) > QA 75 Electronic computers. Computer science|
|Divisions:||Faculties > Science Technology and Medical Studies > School of Engineering and Digital Arts|
|Depositing User:||I.T. Ekpo|
|Date Deposited:||22 May 2009 14:58|
|Last Modified:||22 May 2009 14:58|
|Resource URI:||http://kar.kent.ac.uk/id/eprint/19104 (The current URI for this page, for reference purposes)|
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