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A New Probabilistic Transformation in Generalized Power Space
Authors:Lifang HU  You HE  Xin GUAN  Yong DENG  Deqiang HAN[Author vitae]
Institution:aResearch Institute of Information Fusion, Naval Aeronautical and Astronautical University, Yantai 264001, China;bThe Institute of Electronic Science and Engineering, National University of Defense Technology, Changsha 410073, China;cSchool of Electronics and Information Technology, Shanghai Jiao Tong University, Shanghai 200240, China;dInstitute of Integrated Automation, Xi'an Jiaotong University, Xi'an 710049, China
Abstract:The mapping from the belief to the probability domain is a controversial issue, whose original purpose is to make (hard) decision, but for contrariwise to erroneous widespread idea/claim, this is not the only interest for using such mappings nowadays. Actually the probabilistic transformations of belief mass assignments are very useful in modern multitarget multisensor tracking systems where one deals with soft decisions, especially when precise belief structures are not always available due to the existence of uncertainty in human being's subjective judgments. Therefore, a new probabilistic transformation of interval-valued belief structure is put forward in the generalized power space, in order to build a subjective probability measure from any basic belief assignment defined on any model of the frame of discernment. Several examples are given to show how the new transformation works and we compare it to the main existing transformations proposed in the literature so far. Results are provided to illustrate the rationality and efficiency of this new proposed method making the decision problem simpler.
Keywords:Dempster-Shafer theory  generalized power space  information fusion  interval value  uncertainty
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