neural networks algorithms applications and programming techniques phần 3 docx

neural networks algorithms applications and programming techniques phần 3 docx

neural networks algorithms applications and programming techniques phần 3 docx

... W 23 W 24 W 32 W 33 W 34 W 45 W 42 W 43 W 52 W 53 W 44 W 32 WWW 33 34 35 W W 42 43 W W A , 44 45 Weight matrix: 5th row, 5th column ~ W 55 W 45 W 35 W 25 W 15 W 54 W 44 W 34 W 24 ^14 W 53 W 43 W 33 W 23 W ,3 ^52 W 42 W 32 W 22 WK W S\ W 41 W 3\ tv 21 ^11 Figure ... 13 14 15 "22 ^ 23 ^24 W 25 W 32 ^33 ^34 ^35 ^42 W 43 W 44 W 45 W...

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neural networks algorithms applications and programming techniques phần 4 ppt

neural networks algorithms applications and programming techniques phần 4 ppt

... to the y layer, and update the values on the y-layer units. We shall see how this propagation is done shortly. 3 3. Propagate the updated y information back to the x layer and update the units ... the momentum term discussed in Section 3. 4 .3. Specifically, alpha is the momentum parameter, and delta refers to the weight change values; see Eq. (3. 24). procedure adjust_wei...

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neural networks algorithms applications and programming techniques phần 5 pdf

neural networks algorithms applications and programming techniques phần 5 pdf

... Hopfield and David W. Tank. Computing with neural circuits: A model. Science, 233 :625- 633 , August 1986. [8] Bart Kosko. Adaptive bidirectional associative memories. Applied Optics, 26( 23) :4947-4960, ... have u X i(t + 1) = uxitt) + &u xt (4 .33 ) and vxt = 9Xr(u X i) = ^(l + tanh(Awxi)) (4 .34 ) If we substitute TXI.YJ from Eq. (4 .30 ) into Eq. (4 .31 ), and...

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neural networks algorithms applications and programming techniques phần 6 potx

neural networks algorithms applications and programming techniques phần 6 potx

... Cambridge, MA, pages 614- 634 , 1988. Reprinted from IEEE Transactions of Pattern Analysis and Machine Intelligence PAMI-6: 721-741, 1984. [3] G. E. Hinton and T. J. Sejnowski. Learning and relearning ... Learning in parallel networks. Byte, 10(4):265-2 73, April 1985. [5] S. Kirkpatrick, Jr., C. D. Gelatt, and M. P. Vecchi. Optimization by sim- ulated annealing. In James A....

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neural networks algorithms applications and programming techniques phần 7 pot

neural networks algorithms applications and programming techniques phần 7 pot

... and 12 different input vectors are used to train the network. These 12 vectors represent images of the shuttle at 30 -degree incre- ments (0°, 30 °, , 33 0°). Since there are 12 categories and ... (0,1) (0,2) (0 ,3) (0,4) o o p o o o p l eoe -0+ o o o cf p G o o o ( § )p e o o o o o w, f (c) (1,0) KTO O O O (2 ,3) *, -Q-Q- 0-0 O (3, 3) w -OQ €>KD O O O O O O Figur...

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neural networks algorithms applications and programming techniques phần 8 ppsx

neural networks algorithms applications and programming techniques phần 8 ppsx

... 0.756 0.756 0.756 For F 2 , 00010 00001 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 If we return to the superset vector, ... looks like 00010 0 0 0.75 0 0.75 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .32 9 0 .3...

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neural networks algorithms applications and programming techniques phần 9 pptx

neural networks algorithms applications and programming techniques phần 9 pptx

... 2.0 63 7.220 0.000 5.157 4.126 \ 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 2. 236 \ 2. 236 2. 236 2. 236 2. 236 2. 236 / 32 4 ... 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...

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neural networks algorithms applications and programming techniques phần 10 potx

neural networks algorithms applications and programming techniques phần 10 potx

... 2 63 visual (striate), 37 3 layer IV, 37 5 layer III, 37 5 layer II, 37 5 cost function, 148 Cottrell, G. W., 124 Counterpropagation network (CPN), 2 13- 262, 264, 265, 2 73, 286, 294, 33 1, 34 3, 37 0 architecture ... 182, 184 Grajski, Kamil, 37 1 grandmother cell, 37 5 Grossberg, Stephen, 228, 230 , 232 , 248, 262, 292, 2 93, 297, 299, 31 6, 33 7, 34 2 Hamming distance,...

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