Abstract
The paper presents a method for building-up application adapted topologies for Backpropagation-trained neural networks. We investigate the influence of topology on classification performance and speed by comparing fixed and evolutionary created networks which were trained to recognize handwritten digits.
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György Barna, Kimuno Kaski, Choosing Optimal Network Structure, proceedings of the international Neural Network Conference, Paris 1990
James L. McClelland, David E. Rumelhart, Explorations in Parallel Distributed processing,Vol. 1–3, MIT Press, 3rd revision, 1988
Nigel Dodd, Optimisation of Network Structure Using GeneticTechniques, proceedings of the International Neural Network Conference, Paris 1990
David H. Hubel, Eye, Brain and Vision,Scientific American Library, 1988
Hahn-Ming Lee, Ching-Chi Hsu, Training of a Neural Network with Topology Generation for the Classification Problem, proceedings of the International Neural Network Conference, Paris 1990
Ian D. Longstaff, John F. Cross, A pattern recognition approach to understanding the multilayer perceptron, Pattern Recognition Letters 5 (1987), 315–319, Elsevier North-Holland
Fernando M. Silva, Luis B. Almeida, Speeding up Backpropagation, Advanced Neural Computers, Ed. R. Eckmiller, Elsevier North-Holland, 1990
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© 1991 Springer-Verlag Berlin Heidelberg
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Schiffmann, W., Joost, M., Werner, R. (1991). Performance evaluation of evolutionarily created neural network topologies. In: Schwefel, HP., Männer, R. (eds) Parallel Problem Solving from Nature. PPSN 1990. Lecture Notes in Computer Science, vol 496. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0029764
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DOI: https://doi.org/10.1007/BFb0029764
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