Abstract
Combinatorial optimization is an archaic problem that brings people puzzles until now. This kind of problems are, given the restricted conditions, to consider all risk synthetically, and find the variable that makes the objective function greatest or least. Graph Theory is always used as the mathematical basis for solving this problem. More and more people devote themselves into this area, including many famous genius and amateurs. A classical example is the seven bridges problem [1].
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Konigsberg’s Bridges Problem. http: //www.contracosta.edu/math/Konig.htm. Accessed 22 February 2009
Ranganath HS, Kuntimad G, Johnson JL (1995) Pulse coupled neural networks for image processing. In: Proceedings of IEEE Southeast Conference, Raleigh, 26–29 March 1995
Zhan K, Ma YD, Zhao RC, Feng XW (2009) An efficient algorithm for optimal path problems. Applied Mathematics & Computation (under review)
Eckhorn R, Bauer R, Jordan W et al (1988) Coherent oscillations: a mechanism of feature linking in the visual cortex? Multiple electrode and correlation analyses in the cat. Biological Cybernetics 12(60): 121–130
Eckhorn R, Reitboeck HJ, Arndt M et al (1989) Feature linking via stimulusevoked oscillations: experimental results from cat visual cortex and functional implications from a network model. Neural Networks 6(1): 723–730
Eckhorn R, Reitboeck HJ, Arndt M et al (1990) Feature linking via synchronization among distributed assemblies: simulation of results from cat cortex. Neural Computation 2(3): 293–307
Ma YD, Dai RL, Li L (2002) Image segmentation of embryonic plant cell using pulse-coupled neural networks. Chinese Science Bulletin 47(2): 167–172
Zhang JW, Zhan K, Ma YD (2007) Rotation and scale invariant antinoise PCNN features for content-based image retrieval. Neural Network World 17(2): 121–132
Xu GZ, Zhang ZF, Ma YD (2008) a novel method for iris feature extraction based on interesting cortical model network. Journal of Applied Mathematics & Computing 26(1): 341–352
Wang ZB, Ma YD, Cheng FY, Yang LZ (2010) Review of Pulse Coupled Neural Networks. Image and Vision Computing 28(1): 5–13
Caulfield HJ, Kinser JM (1999) Finding the shortest path in the shortest time using PCNNs. IEEE Transactions on Neural Networks 10(3): 604–606
Hong Q, Zhang Y (2007) A new algorithm for finding the shortest paths using PCNN. Chaos, Solitons & Fractals 33(4): 1220–1229
Zhao RC, Ma YD, Zhan K (2008) Three-state cascading pulse coupled neural network and the application in finding shortest paths. Systems Engineering and Electronics 30(9): 1785–1789
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2010 Higher Education Press, Beijing and Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Ma, Y., Zhan, K., Wang, Z. (2010). Combinatorial Optimization. In: Applications of Pulse-Coupled Neural Networks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13745-7_8
Download citation
DOI: https://doi.org/10.1007/978-3-642-13745-7_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13744-0
Online ISBN: 978-3-642-13745-7
eBook Packages: Computer ScienceComputer Science (R0)