A learning rule for very simple universal approximators consisting of a single layer of perceptrons∗ Peter Auer1, Harald Burgsteiner2,†, Wolfgang Maass3 - Igi - Document - PDFSEARCH.IO - Document Search Engine

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	A learning rule for very simple universal approximators consisting of a single layer of perceptrons∗ Peter Auer1, Harald Burgsteiner2,†, Wolfgang Maass3 Add to Reading List Document Date: 2008-04-03 08:53:39 Open Document File Size: 216,42 KB Share Result on Facebook City Graz / Leoben / / Country Austria / / Currency pence / / / Facility Theoretical Computer Science Graz University / Information Technology University of Leoben Franz-Josef-Strasse / Department of Health Care Engineering Graz University of Applied Sciences Eggenberger Allee / / IndustryTerm purpose hardware / large backpropagation networks / analyzed online learning / perceptron learning algorithm / feedforward neural networks / biological networks / neural networks / distributed learning algorithm / gradient descent learning algorithm / biological neural systems / noisy analog computing elements / feedforward networks / explicit algorithm / Possible applications / usual vector product / learning algorithm / learning algorithms / / Organization Department of Health Care Engineering Graz University of Applied Sciences Eggenberger Allee / Information Technology University of Leoben Franz-Josef-Strasse / European Union / Theoretical Computer Science Graz University of Technology Inffeldgasse / / Position Chair / Corresponding Author / / ProgrammingLanguage PASCAL / / Technology learning algorithm / analog computing / distributed learning algorithm / Information Technology / gradient descent learning algorithm / learning algorithms / machine learning / explicit algorithm / 5 Learning algorithms / perceptron learning algorithm / / SocialTag Learning Perceptron Feedforward neural network Multilayer perceptron Artificial neuron ADALINE Delta rule Activation function Backpropagation Neural networks