Enhanced artificial neurons for network applications

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Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/3922

Title: Enhanced artificial neurons for network applications
Author(s): Murray, Gerard; Hendtlass, Tim
Abstract: It is hypothesised that conventional back propagation networks have limitations arising at least, from the simplicity of the artificial neuron model that is used. A more complex neuron, called a micronet, to distinguish it from the conventional neuron, is introduced. The architecture and heuristic of the micronet are described. Visual examples of the complex decision surfaces that can be produced by a single micronet in response to a range of problems are presented.
Publication type: Conference paper
Research centre: Swinburne University of Technology. School of Biophysical Science and Electrical Engineering. Centre for Intelligent Systems and Complex Processes
Source: Lecture notes in computer science : engineering of intelligent systems : Proceedings of the 14th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems (IEA/AIE 2001), Budapest, Hungary, 04-07 June 2001, Vol. 2070 (2001), pp. 281-289
Publication year: 2001
Publisher: Springer-Verlag
ISBN: 9783540422198
Publisher URL: http://dx.doi.org/10.1007/3-540-45517-5_32
Peer reviewed