neural networks algorithms applications and programming techniques phần 9 pptx
neural networks algorithms applications and programming techniques phần 9 pptx
... here, however, as both u, and q are now nonzero. Beginningagain at w, we find:w = (2.263,7 .92 0,0.100,5.657,4.526)'x = (0.206,0.722,0.0 09, 0.516,0.413)*v = (2.2 69, 7 .94 2,0.000,5.673,4.538)'where ... parameter for network} 9. 2 Architectures of Spatiotemporal Networks (STNs)351*4 = yFigure 9. 8 In this sequence, the network is the same as that shown inFigure 9. 7, as are the input patterns. ... smallwords and large words? Moreover, some words are subsets of other words;will the system distinguish between a subset word spoken slowly and a superset 9. 2 Architectures of Spatiotemporal Networks...
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neural networks algorithms applications and programming techniques phần 2 pptx
... editor. Neural Networks and Natural Intelligence. MITPress, Cambridge, MA, 198 8. [9] Stephen Grossberg. Nonlinear neural networks: Principles, mechanisms, and architectures. Neural Networks, ... Reading,MA, 199 0.[17] C. Klimasauskas. The 198 9 N'euro-Computing Bibliography, MIT Press,Cambridge, MA, 198 9.[18]Teuvo Kohonen. An introduction to neural computing. Neural Networks, 1(1):3-16, ... between neural net and conventional classifiers. In Proceedings of the IEEE First Interna-tional Conference on Neural Networks, San Diego, CA, pp. iv.485-iv. 494 June 198 7.[15]Willian Y. Huang and...
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neural networks algorithms applications and programming techniques phần 1 ppt
... in terms of sequential algorithms. Many problems are not suited to this approach, however, causing us to expend Neural Networks Algorithms, Applications, and Programming Techniques James A. FreemanDavid ... Processing 2657.2 Applications of Self-Organizing Maps 2747.3 Simulating the SOM 2 79 Bibliography 2 89 Chapter 8Adaptive Resonance Theory 297 8.1 ART Network Description 293 8.2 ART1 298 8.3 ART2 ... studying and implementing simple resistive networks forcomputing motion, stereo, and color in biological and artificial systems.Acknowledgments ixproceedings. In particular, the journals Neural Networks, ...
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neural networks algorithms applications and programming techniques phần 3 docx
... International Conference on Neural Networks, San Diego,June 198 8.3.2 The Generalized Delta Rule 95 In this situation, the power of a neural network to discover its own algorithms is extremely ... Arobust algorithm for training analog neural networks. In Proceedings ofthe International Joint Conference on Neural Networks, pages I-533-I-536, January 199 0.[3] Richard W. Hamming. Digital ... Cliffs, NJ, 197 5.[6] Bernard Widrow and Marcian E. Hoff. Adaptive switching circuits. In 796 0IRE WESCON Convention Record, New York, pages 96 -104, 196 0. IRE.[7] Bernard Widrow and Rodney...
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neural networks algorithms applications and programming techniques phần 4 ppt
... sonar targets. Neural Networks, 1(1):76 -90 , 198 8.[4] Robert Hecht-Nielsen. Neurocomputing. Addison-Wesley, Reading, MA, 199 0.[5] Geoffrey E. Hinton and Terrence J. Sejnowski. Neural network ... Seattle, WA, July 198 7.[6] James McClelland and David Rumelhart. Explorations in Parallel Dis-tributed Processing. MIT Press, Cambridge, MA, 198 6.[7] James McClelland and David Rumelhart. ... April 198 5. [9] Terrence J. Sejnowski and Charles R. Rosenberg. Parallel networks thatlearn to pronounce English text. Complex Systems, 1:145-168, 198 7.[10] Philip D. Wasserman. Neural Computing:...
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neural networks algorithms applications and programming techniques phần 5 pdf
... Modeling. Academic Press,Orlando, FL, 198 7.[2] M. R. Garey and D. S. Johnson. Computers and Intractability. W. H.Freeman, New York, 197 9.[3] Morris W. Hirsch and Stephen Smale. Differential ... December 198 7. [9] Bart Kosko. Competitive bidirectional associative memories. In Proceed-ings of the IEEE First International Conference on Neural Networks, SanDiego, CA, II: 7 59- 766, June 198 7.[lOJBart ... 81:3088-3 092 , May 198 4. Biophysics.[6] John J. Hopfield and David W. Tank. " ;Neural& quot; computation of decisionsin optimization problems. Biological Cybernetics, 52:141-152, 198 5.[7]...
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neural networks algorithms applications and programming techniques phần 6 potx
... Cognitive Science 9: 147-1 69, 198 5.[2] Stuart Geman and Donald Geman. Stochastic relaxation, Gibbs distribu-tions, and the Bayesian restoration of images. In James A. Anderson and Edward Rosenfeld, ... pages 614-634, 198 8. Reprinted from IEEE Transactions of PatternAnalysis and Machine Intelligence PAMI-6: 721-741, 198 4.[3] G. E. Hinton and T. J. Sejnowski. Learning and relearning in ... Learning in parallel networks. Byte, 10(4):265-273,April 198 5.[5] S. Kirkpatrick, Jr., C. D. Gelatt, and M. P. Vecchi. Optimization by sim-ulated annealing. In James A. Anderson and Edward Rosenfeld,...
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neural networks algorithms applications and programming techniques phần 7 pot
... television monitor, and robot all interfaceto a desktop computer that simulates the neural network and houses a videoframe-grabber board. The architecture is an example of how a neural networkcan ... spacecraft-orientation data, and exer-cise the simulator in both the forward-propagation and counterpropagationmodes. How well does the simulator produce the desired input pattern whengiven sine and cosine ... Simulator2 49 outsweightsFigure 6.24 The complete data structure for the CPN is shown. Thesestructures are representative of all the layered networks thatwe simulate in this text.computed and used...
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neural networks algorithms applications and programming techniques phần 8 ppsx
... 0.756 0.756For F2,00010000010.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 If we return to the superset vector, ... looks like000100 0 0.75 0 0.750.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 0.3 29 Now let's see what happens when ... lessthan L/(L - 1 + M). Each weight is given the value 0.4 29 -0.1= 0.3 29. Eachweight vector is thenZj = (0.3 29, 0.3 29, 0.3 29, 0.3 29, 0.3 29) 'All F2 units are initialized to zero activity....
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neural networks algorithms applications and programming techniques phần 10 potx
... 59, 62, 83, 96 , 100gradient-descent method, 60, 95 , 97 , 99 , 105,170, 182, 184Grajski, Kamil, 371grandmother cell, 375Grossberg, Stephen, 228, 230, 232, 248, 262, 292 , 293 , 297 , 299 , ... of, 1 69 motor, 263output, 225partition, 175, 186probability density, 270quadratic output, 227, 2 29 quenching, 19 sigmoid, 98 , 99 , 103, 114, 144, 145, 146,227, 230, 3 19 gain, 19, 392 gain ... propagation, 197 simulator, 1 89, 204brain, 263, 293 , 376Butler, Charles, 41bytes, 171Carpenter, Gail A., 292 , 299 , 316, 3 19, 337,338Cauchydistribution, 1 89, 212machine, 1 89 Caudill, Maureen,...
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