Self-organization in CNN-based object nets

2010 12th International Workshop on Cellular Nanoscale Networks and their Applications, CNNA 2010

Volumn , Issue , 2010, Pages

  Werbos, Ludmilla ^a   Werbos, Paul ^b  

^a IntControl   (United States)

^b UNIVERSITY OF MEMPHIS   (United States)

Author keywords

Learning; Object nets

Indexed keywords

DECISION MAKING; ELECTRIC POWER SYSTEM CONTROL; ELECTRIC POWER TRANSMISSION NETWORKS; IMAGE RECOGNITION; LEARNING ALGORITHMS; NANOTECHNOLOGY; RECURRENT NEURAL NETWORKS;

CELLULAR SIMULTANEOUS RECURRENT NETWORKS; ELECTRIC POWER GRIDS; INPUT-OUTPUT RELATIONS; LEARNING; MULTI LAYER PERCEPTRON; OBJECT NETS; OPTIMAL DECISION MAKING; UNIVERSAL APPROXIMATORS;

CELLULAR NEURAL NETWORKS;

EID: 77952353502     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/cnna.2010.5430292     Document Type: Conference Paper

References (13)

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4. P. Werbos, Object Nets, Patent number 6, 708, 160 USPTO.
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7. Also see Nicolelis, M., Lin, C., Woodward, D. & Chapin, J. (1993). Induction of immediate spatiotemporal changes in thalamic networks by peripheral block of ascending cutaneous information, Nature, Vol. 361, 11 Feb. 1993, pp. 533-536.
8. Mallot, H.A. (1995): "Layered Computation in Neural Networks.", In: M.A. Arbib (Ed.) The Handbook of Brain Theory and Neural Networks. Cambridge MA: The MIT Press.
9. R. Ilin, R. Kozma, P.J. Werbos, "Beyond Feedforward Models Trained by Backpropagation: A Practical Training Tool for a More Efficient Universal Approximator", IEEE Transactions on Neural Networks. Vol. 19, No.6, June 2008. pp. 929-937.
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11. C. Goller and A. Kuchler, "Learning task-dependent distributed structure-representations by backpropagation through structure, " in IEEE International Conference on Neural Networks, pp. 347-352, 1996.
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13. See also P.Werbos, Intelligence in the Brain: A theory of how it works and how to build it, Neural Networks, Volume 22, Issue 3, April 2009, pp. 200-212.