neural networks algorithms applications and programming techniques phần 8 ppsx

... of Eq. (8. 12), we must have D\ - B\ < 0, or B l > D l (8. 13) Equations (8. 10), (8. 11), and (8. 13) combine to give the overall condition, max{D,,l} < B\ < D } + 1 (8. 14) The ... inhibitory input to each unit is (8. 17) (8. 18) Substituting these values into Eq. (8. 1) yields ± 2 j = -x 2j + (1 - A 2 x 2J )(D 2 Tj + g(x 2j )) - (B 2 (8. 19) 8. 2...

Ngày tải lên: 12/08/2014, 21:21

... 265 7.2 Applications of Self-Organizing Maps 274 7.3 Simulating the SOM 279 Bibliography 289 Chapter 8 Adaptive Resonance Theory 297 8. 1 ART Network Description 293 8. 2 ART1 2 98 8.3 ART2 316 8. 4 ... in terms of sequential algorithms. Many problems are not suited to this approach, however, causing us to expend Neural Networks Algorithms, Applications, and Programming...

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... editor. Neural Networks and Natural Intelligence. MIT Press, Cambridge, MA, 1 988 . [9] Stephen Grossberg. Nonlinear neural networks: Principles, mechanisms, and architectures. Neural Networks, ... Klimasauskas. The 1 989 N'euro-Computing Bibliography, MIT Press, Cambridge, MA, 1 989 . [ 18] Teuvo Kohonen. An introduction to neural computing. Neural Networks,...

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... counter} Bibliography 87 [8] Rodney Winter and Bernard Widrow. MADALINE RULE II: A training algorithm for neural networks. In Proceedings of the IEEE Second In- ternational Conference on Neural Networks, ... 1 988 . [2] David Andes, Bernard Widrow, Michael Lehr, and Eric Wan. MRIII: A robust algorithm for training analog neural networks. In Proceedings of the Internat...

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... MP2, AAAI87, Seattle, WA, July 1 987 . [6] James McClelland and David Rumelhart. Explorations in Parallel Dis- tributed Processing. MIT Press, Cambridge, MA, 1 986 . [7] James McClelland and David ... sonar targets. Neural Networks, 1(1):76-90, 1 988 . [4] Robert Hecht-Nielsen. Neurocomputing. Addison-Wesley, Reading, MA, 1990. [5] Geoffrey E. Hinton and Terrence J. Sejnowski....

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... Conference on Neural Networks, San Diego, CA, II: 759-766, June 1 987 . [lOJBart Kosko. Constructing an associative memory. Byte, 12(10): 137-144, September 1 987 . 1 58 The BAM and the Hopfield ... 79:2554- 25 58, April 1 982 . Biophysics. [5] John J. Hopfield. Neurons with graded response have collective computa- tional properties like those of two-state neurons. Proc. Natl....

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... Hinton, and Terrence J. Sejnowski. A learning algorithm for Boltzmann machines. In James A. Anderson and Edward Rosenfeld, editors, Neurocomputing. MIT Press, Cambridge, MA, pages 6 38- 650, 1 988 . ... pages 614-634, 1 988 . Reprinted from IEEE Transactions of Pattern Analysis and Machine Intelligence PAMI-6: 721-741, 1 984 . [3] G. E. Hinton and T. J. Sejnowski. Learning a...

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... distinguish and are most prone to misclassification by the network. Source: Reprinted with permission from Teuvo Kohonen, ''The neural phonetic typewriter." IEEE Computer, March 1 988 . ... television monitor, and robot all interface to a desktop computer that simulates the neural network and houses a video frame-grabber board. The architecture is an example of ho...

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... u and p. First, note that, if u and p are parallel, then Eq. (8. 48) reduces to ||r|| — 1, and there will be no reset. As long as there is no output from F 2 , Eq. (8. 37) shows that u = p, and there ... following equations: w, = Ii+ aui (8. 33) Xl = e +L\\ (8 ' 34) v t = /(I*) + bf(q t ) (8. 35) (8. 36) (yi)zn (8. 37) q t = —p-77 (8. 38) e + IIPlI We shall...

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... 19 sigmoid, 98, 99, 103, 114, 144, 145, 146, 227, 230, 319 gain, 19, 392 gain parameter, 144, 145, 1 48 Gaussiin function, 2 78 Gelatt.lc. D., 212 Gemani Donald, 188 , 189 Geman, Stuart, 188 , 189 generalization, ... January-February 1 988 . [9] Ronald J. Williams and David Zipser. A learning algorithm for continually running fully recurrent neural networks. Neural Computa...

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