neural networks algorithms applications and programming techniques phần 10 potx

... of Eq. (1,0 .10) . Also substitute Eq. (10. 12) in Eq. (10. 10) and notice the similarity between the numerator and denominator of the first term in the brackets. Equation^ (10. 12) indicates ... 247 data structures, 248 learning algorithms, 254 production algorithms, 251 training, 236 crosstalk, 133, 135 Index 397 data compression, 107 , 210 delta rule, 96, 101 dendrites...

Ngày tải lên: 12/08/2014, 21:21

... Pattern Analysis and Machine Intelligence PAMI-6: 721-741, 1984. [3] G. E. Hinton and T. J. Sejnowski. Learning and relearning in Boltzmann machines. In David E. Rumelhart and James L. McClelland, ... Learning in parallel networks. Byte, 10( 4):265-273, April 1985. [5] S. Kirkpatrick, Jr., C. D. Gelatt, and M. P. Vecchi. Optimization by sim- ulated annealing. In James A. And...

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... 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. Freeman David ... understanding of the operation of the specific networks presented • The ability to program simulations of those networks successfully • The ability to apply neural ne...

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... Eckmiller and Christoph v. d. Malsburg, editors. Neural Computers. NATO ASI Series F: Computer and Systems Sciences. Springer-Verlag, Berlin, 1988. [8] Stephen Grossberg, editor. Neural Networks and ... Cambridge, MA, 1988. [9] Stephen Grossberg. Nonlinear neural networks: Principles, mechanisms, and architectures. Neural Networks, 1(1): 17-62, 1988. [10] Donald O....

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... byte; end record; = 0 0100 1 0101 00011111 1100 0 1100 0 1100 01 = 0951FC631 16 = 65 10 ASCII Figure 3.2 Each character image is mapped to its corresponding ASCII code. 86 Adaline and Madaline Programming Exercises 2.1. ... David Andes, Bernard Widrow, Michael Lehr, and Eric Wan. MRIII: A robust algorithm for training analog neural networks. In Proceedings of the International...

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... states that have each city only once on the tour. B 0100 0 100 00 00 010 00001 0 0100 (a) 1 2345 0100 0 A 100 00 B 00 010 C 00001 D 0 0100 E (b) Figure 4 .10 (a) In this representation scheme for the output ... Sejnowski and Charles R. Rosenberg. Parallel networks that learn to pronounce English text. Complex Systems, 1:145-168, 1987. [10] Philip D. Wasserman. Neural Comput...

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... memory Row 5 Row 4 Row 3 Row 2 Row 1 RowO Y////////A BA + 6 (10) BA + 5 (10) BA + 4 (10) BA + 3 (10) BA + 2 (10) BA+1 (10) 10 Columns Base address (BA) Low memory Figure 4.13 The row-major ... neural networks discussed in Chapters 2, 3, and 4 relied on the minimiza- tion of some function during either the learning process (Adaline and back- propagation) or the recall...

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... .X xxxxx = 0 0100 0101 0 100 01 11111 100 01 100 01 X. . .X X. . .X 6.2. Without resizing the network, retrain the CPN described in Programming Exercise 6.1 to recognize both the upper- and lowercase ... describe the results. . .x. . . . x. . . .x. . .xxx. = 0 0100 0 0100 0 0100 OHIO 11111 xxxxx 6.5. Describe what would happen in Programming Exercise 6.4 if you only allowe...

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... various learning methods for neural networks, as well as a review of the necessary mathematics. Bibliography [1] Willian Y. Huang and Richard P. Lippmann. Neural net and traditional classifiers. ... visuo-motor-coordination. Neural Networks, 2(3): 159-168, 1989. 7.2 Applications of Self-Organizing Maps 277 Figure 7.11 This figure shows a schematic of a simple robot arm and...

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... cycle counter to one, and return to step 2. If there is no reset, and the cycle counter is one, increment the cycle counter and continue with step 11. If there is no reset, and the cycle counter ... 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 th...

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