Index 220 09 (6) 220 09 (5) 26 (223) Tolkien J. R. R. hobbit 02 (647) CH25 (12) 04 (487) noc maxefekt (4) Sandemo Margit Saga O Ludziach Lodu |
[ Pobierz całość w formacie PDF ] .bnrn is the name we give to the array of neurons in the second layer and bnmbr denotes the size of that array.The sequence of operations in the program are as follows: We ask the user to input the exemplar vector pair. We give the network the X vector, in the exemplar pair.We find the activations of the elements of bnrn array and get corresponding output vector as a binary pattern.If this is the Y in the exemplar pair, the network has made a desired association in one direction, and we go on to the next.step.Otherwise we have a potential associated pair, one of which is X and the other is what we just got as the output vector in the opposite layer.We say potential associated pair because we have the next step to confirm the association. We run the bnrn array through the transpose of the weight matrix and calculate the outputs of the anrn array elements.If, as a result, we get the vector X as the anrn array, we found an associated pair, (X, Y).Otherwise, we repeat the two steps just described until we find an associated pair. We now work with the next pair of exemplar vectors in the same manner as above, to find an associated pair. We assign serial numbers, denoted by the variable idn, to the associated pairs so we can print them all together at the end of the program.The pair is called (X, Y) where X produces Y through the weight matrix W, and Y produces X through the weight matrix, which is the transpose of W. A flag is used to have value 0 until confirmation of association is obtained, when the value of the flag changes to 1. Functions compr1 and compr2 in the network class verify if the potential pair is indeed an associated pair and set the proper value of the flag mentioned above. Functions comput1 and comput2 in the network class carry out the calculations to get the activations and then find the output vector, in the respective directions of the fuzzy associative memory network.A lot of the code from the bidirectional associative memory (BAM) is used for the FAM.Here are the listings, with comments added where there are differences between this code and the code for the BAM of Chapter 8.PreviousTable of ContentsNext | | Use of this site is subject to certain ,All rights reserved.Reproduction whole or in part in any form or medium without express written permision of EarthWeb is prohibited [ Pobierz całość w formacie PDF ] |
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