DocumentCode
3391108
Title
Research on the neural networks and the geodetic number of the graph
Author
Cao, Jianxiang ; Wu, Bin ; Shi, Minyong
Author_Institution
Sch. of Comput. Sci., Commun. Univ. of China, Beijing, China
fYear
2009
fDate
15-17 June 2009
Firstpage
418
Lastpage
421
Abstract
Graph theory is the fundamental basis of the neural networks. This paper reports the investigation work of the relationships between artificial neural networks and graph theory, and presents the analysis of the specific issues relating to the change of the geodetic number due to operations on the graphs. Recent research work on the geodetic number of graphs has been found in the literature. Determining the geodetic number of arbitrary graph can be proved to be NP-hard. However, a fundamental issue in graph theory concerns how a parameter value is affected after small changes executed to the graph. This issue is analyzed in the authors´ research by adding or contracting an edge to the graph.
Keywords
computational complexity; graph theory; neural nets; NP-hard problem; artificial neural networks; geodetic number; graph theory; Animation; Artificial neural networks; Biological neural networks; Biological system modeling; Computer science; Feedforward neural networks; Graph theory; Neural networks; Neurons; Software libraries; geodesic; geodetic number; geodetic set; neural network;
fLanguage
English
Publisher
ieee
Conference_Titel
Cognitive Informatics, 2009. ICCI '09. 8th IEEE International Conference on
Conference_Location
Kowloon, Hong Kong
Print_ISBN
978-1-4244-4642-1
Type
conf
DOI
10.1109/COGINF.2009.5250702
Filename
5250702
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