摘要
建立了一种用于信息融合的熵模型 ,依据融合的几个步骤即信息提取、关联与决策 ,描述了基于熵模型进行信息自适应融合的新方法·该方法可对从各对象源 (如传感器、数据库、知识库等 )中提取的特征属性信息进行模型化 ,对这些模型化的属性信息进行关联后 ,得到准确的决策·为了实现多对象源的信息融合 ,提出了EAA算法·该算法基于熵自适应聚集规则 ,通过缩减关联模型联合动作的复杂性来控制其收敛性·并通过应用实例 。
A kind of entropy model for information fusion was proposed. According to fusion steps, information detection, association, decision, the new fusion approach based on the entropy model was described. This method can model the character property information from multi sources such as sensors, database, repository, and by associating these information the decision can be gained. In order to realize multi object information fusion, an algorithm called EAA for fusion problem was developed based on the entropy adaptive aggregation law. The algorithm controls it's convergence by reducting the complexity of the action of association model.
出处
《东北大学学报（自然科学版）》
EI
CAS
CSCD
北大核心
2002年第3期232-235,共4页
Journal of Northeastern University(Natural Science)
基金
国家自然科学基金资助项目 (69873 0 0 7)
关键词
自适应融合
信息表示
关联
决策
熵模型
adaptive fusion
information representation
association
decision making
entropy model
