Zenghui Hu

Work place: College of Electronic Science and Technology, National University of Defense Technology, Changsha, China

E-mail: zhhunudt@163.com


Research Interests: Computational Complexity Theory, Detection Theory


Zenghui  Hu was  born  in  Pingxiang,  Jiangxi  province,  in 1982. He obtained his bachelor degree of science and Master Degree   of  science   in   2004   and   2006,   respectively,   from National University of Defense Technology, Changsha, Hunan, China.
He is now a Ph.D. candidate in the College of Electrical Science   and  Engineering,  National  University   of  Defense Technology.   His   research   interests   include   blind   source separation, array signal processing, evidence theory etc.

Author Articles
Clustering Belief Functions using Extended Agglomerative Algorithm

By Ying Peng Huairong Shen Zenghui Hu Yongyi Ma

DOI: https://doi.org/10.5815/ijigsp.2011.01.05, Pub. Date: 8 Feb. 2011

Clustering belief functions is not easy because of uncertainty and the unknown number of clusters. To overcome this problem, we extend agglomerative algorithm for clustering belief functions. By this extended algorithm, belief distance is taken as dissimilarity measure between two belief functions, and the complete-link algorithm is selected to calculate the dissimilarity between two clusters. Before every merging of two clusters, consistency test is executed. Only when the two clusters are consistent, they can merge, otherwise, dissimilarity between them is set to the largest value, which prevents them from merging and assists to determine the number of final clusters. Typical illustration shows same promising results. Firstly, the extended algorithm itself can determine the number of clusters instead of needing to set it in advance. Secondly, the extended algorithm can deal with belief functions with hidden conflict. At last, the algorithm extended is robust.

[...] Read more.
Other Articles