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@INPROCEEDINGS{Moerland-95.1,
         author = {Moerland, Perry and Fiesler, Emile and Saxena, Indu},
         editor = {Fogelman-Souli{\'{e}}, F. and Gallinari, P.},
       projects = {Idiap},
          title = {The Effects of Optical Thresholding in Backpropagation Neural Networks},
      booktitle = {Proceedings of the International Conference on Artificial Neural Networks (ICANN'95 and NeuroN{\^{\i}}mes'95)},
         volume = {2},
        chapter = {Session 2},
           year = {1995},
      publisher = {EC2 & Cie},
       location = {Paris, France},
   organization = {ENNS},
        address = {Paris La D{\'{e}}fense, France},
           isbn = {2-910085-19-8},
       abstract = {Sigmoid-like activation functions implemented in analog hardware differ in various ways from the standard sigmoidal function as they are asymmetric, truncated, and have a non-standard gain. It is demonstrated how one can adapt the backpropagation learning rule to compensate for these non-standard sigmoids as available in hardware. This method is applied to multilayer neural networks with all-optical forward propagation and liquid crystal light valves (LCLV) as optical thresholding devices. In this paper the results of software simulations of a backpropagation neural network with five different LCLV activation functions are presented and it is shown that the adapted learning rule performs well with these LCLV curves},
dates={October 9--13, 1995}, language={English}, ipdmembership={neuron learning},
}