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.
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Murray, G., Hendtlass, T. (2001). Enhanced Artificial Neurons for Network Applications. In: Monostori, L., Váncza, J., Ali, M. (eds) Engineering of Intelligent Systems. IEA/AIE 2001. Lecture Notes in Computer Science(), vol 2070. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45517-5_32
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DOI: https://doi.org/10.1007/3-540-45517-5_32
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