neural networks algorithms applications and programming techniques phần 1 ppt
neural networks algorithms applications and programming techniques phần 1 ppt
... Technology Output Output 0 0 1 1 0 1 0 1 0 1 1 0 Inputs Figure 1. 15 This two-layer network has two nodes on the input layer with input values x\ and x 2 that can take on values of 0 or 1. We would like ... Hopfield Memory 14 1 4.4 Simulating the BAM 15 6 Bibliography 16 7 Chapter 5 Simulated Annealing 769 5 .1 Information Theory and Statistical Mechanics 17 1 5.2...
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neural networks algorithms applications and programming techniques phần 2 pptx
... convey 2 .1 Review of Signal Processing 47 1. 0 0.5 (a) -0.5 -1. 0 0.05 0 .1 0 .15 0.2 Carrier wave (b) (c) 0.05 0 .1 0 .15 Wave containing information 0.05 0 .1 0 .15 0.2 1. 3 1. 2 1. 1 0.9 0.8 0.7 1. 5 1. 0 0.5 -0.5 -1. 0 -1. 5 Amplitude-modulated ... April 19 87. [ 21] Ronald J. MacGregor. Neural and Brain Modeling. Academic Press, San Diego, CA, 19 87. 52 Adaline a...
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neural networks algorithms applications and programming techniques phần 4 ppt
... =(!,-!, -1, 1, -1, 1)* and x 2 = (1, 1 ,1, -1, -1, -1) * Determine the output using XQ = (1, 1 ,1, 1, 1, 1)*, which is a Hamming dis- tance of two from each training vector. Try XQ = ( 1, 1 ,1, 1, 1, 1) ', ... — (4, -12 , -12 , -12 ,-4 ,12 )*. The new y vector is y new = (1, -1, -1, -1, -1, 1) ', which is also one of the training vectors. Propagating back t...
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neural networks algorithms applications and programming techniques phần 9 pptx
... = (4 .15 1,4 .15 1,4 .15 1,4 .15 1,4 .15 1,4 .15 1)' Because all of the activities are the same, the first unit becomes the winner and the activity vector becomes T = (4 .15 1,0,0,0,0,0)' and the ... (0.205,0. 718 ,0 .10 3,0. 513 ,0. 410 )' v = (0.205,0. 718 ,0.000,0. 513 ,0. 410 )' u = (0.206,0.722,0.000,0. 516 ,0. 413 )' p = (0.206,0.722,0.000,0. 516 ,0. 413...
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neural networks algorithms applications and programming techniques phần 3 docx
... 0 010 010 1 010 0 011 111 110 0 011 00 011 00 01 = 0951FC6 31 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. ... derivation is contained in a 19 60 paper by Widrow and Hoff [6], which is also reprinted in the collection edited by Anderson and Rosenfeld [1] . Bibliography [1] Jam...
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neural networks algorithms applications and programming techniques phần 5 pdf
... assign equal probabilities to each of the four vectors, such that P {1, 0,0} = 10 %, P {1, 0 ,1} = 10 %, P {1, 1,0} = 10 %, P {1, 1 ,1} = 10 %. The rationale for this choice is that the information available ... probability of 40 percent for the occurrence of +1 in the first position. One example is P{ 1, 0,0} = 10 %, P {1, 0 ,1} = 4%, P {1, 1,0} = 8%, P {1, 1 ,1} =...
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neural networks algorithms applications and programming techniques phần 6 potx
... Intelligence PAMI-6: 7 21- 7 41, 19 84. [3] G. E. Hinton and T. J. Sejnowski. Learning and relearning in Boltzmann machines. In David E. Rumelhart and James L. McClelland, editors, Parallel Distributed ... Cambridge, MA, pages 638-650, 19 88. Reprinted from Cognitive Science 9 :14 7 -16 9, 19 85. [2] Stuart Geman and Donald Geman. Stochastic relaxation, Gibbs distribu...
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neural networks algorithms applications and programming techniques phần 7 pot
... .X xxxxx = 0 010 0 010 10 10 0 01 111 11 100 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. = 0 010 0 0 010 0 0 010 0 OHIO 11 111 xxxxx 6.5. Describe what would happen in Programming Exercise 6.4 if you...
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neural networks algorithms applications and programming techniques phần 8 ppsx
... (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 ART1 ... visuo-motor-coordination. Neural Networks, 2(3): 15 9 -16 8, 19 89. 7.2 Applications of Self-Organizing Maps 277 Figure 7 .11 This figure shows a schematic of a simple...
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neural networks algorithms applications and programming techniques phần 10 potx
... Morris, 13 7 Hoff, Marcian E., 86 homunculus, 263, 264 Hopfield, John J., 41, 12 7, 15 5, 15 7, 16 7, 16 9, 19 0 Hopfield memory (network), 12 7, 14 1 -15 7, 17 0, 17 8 continuous, 14 1, 14 4, 14 6 discrete, 14 1 high-gain ... 17 1 Boltzmann 17 9- 212 algorithms, 19 6 completion network, 17 9, 18 0 constant, 17 5 data structures, 19 0 distribution, 17 5, 17 8 fa...
Ngày tải lên: 12/08/2014, 21:21