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
Link To Document :
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