Michael Fleisher

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Abst ract . Learning in layered neu ral networks is posed as the minimizat ion of an error function defined over the training set. A probabilist ic interpretation of the target act ivities suggests the use of relat ive ent ropy as an error measure. We investigate t he merits of using this error function over t he traditional quad ratic function for gradient(More)
A novel technique is described herein to perform a laparoscopic varicocelectomy using the high-ligation modified Palomo technique. The variation in this case is the preservation of lymphatic drainage by intraoperative identification of the lymphatics using intratesticular injection of methylene blue dye.
THE HOPFIELD MODEL WITH MUL TI-LEVEL NEURONS Michael Fleisher Department of Electrical Engineering Technion Israel Institute of Technology Haifa 32000, Israel The Hopfield neural network. model for associative memory is generalized. The generalization replaces two state neurons by neurons taking a richer set of values. Two classes of neuron input output(More)
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