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ShihYi Yuan, SyYen Kuo, "A New Technique for Optimization Problems in Graph Theory," IEEE Transactions on Computers, vol. 47, no. 2, pp. 190196, February, 1998.  
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@article{ 10.1109/12.663765, author = {ShihYi Yuan and SyYen Kuo}, title = {A New Technique for Optimization Problems in Graph Theory}, journal ={IEEE Transactions on Computers}, volume = {47}, number = {2}, issn = {00189340}, year = {1998}, pages = {190196}, doi = {http://doi.ieeecomputersociety.org/10.1109/12.663765}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Computers TI  A New Technique for Optimization Problems in Graph Theory IS  2 SN  00189340 SP190 EP196 EPD  190196 A1  ShihYi Yuan, A1  SyYen Kuo, PY  1998 KW  Vertex cover KW  maximum independent set KW  maximum clique KW  neural network KW  Hopfield model. VL  47 JA  IEEE Transactions on Computers ER   
Abstract—This paper presents an efficient technique to map the minimum vertex cover and two closely related problems (maximum independent set and maximum clique) onto the Hopfield neural networks. The proposed approach can be used to find nearoptimum solutions for these problems in parallel, and particularly the network algorithm always yields minimal vertex covers. A systematic way of deriving energy functions is described. Based on these relationships, other NPcomplete problems in graph theory can also be solved by neural networks. Extensive simulations were performed, and the experimental results show that the network algorithm outperforms the wellknown greedy algorithm for vertex cover problems.
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