摘要
多特征融合是将各种信息以某种优化准则组合起来,产生对观测目标的一致性解释和描述,从而形成比单一信息源更精取、更完整的估计和判决;文章重点研究了Dempster-Shafer证据理论,讨论了它的可应用性,在此基础上把决策融合策略与模糊自适应共振(FART)神经网络、所获取的特征知识相结合,实现了对三类目标的分类识别,实验表明通过决策融合后可使识别率比原来提高2%左右,提高了识别的可靠性,显示了该方法在实现水中目标识别上的重要应用前景。
Many features fusion is all kinds of information in some rule of optimization combined, the consistency of the description and interpretation is given, so as to form more than a single source of pure take, more complete estimation and judgment. This article focuses on Dempster--Shafer evidence theory, discusses the application of it, and based on this, the decision fusion strategy and fuzzy adaptive reso- nance (FART) neural network, and the characteristics of combining for knowledge, realize the goal of three kinds of classification, the ex- periment that through decision fusion can make the recognition rate than the original increased 2~ or so, improve the reliability of the recog- nition, shows that the method in the realization of the target recognition of important on the application prospect.
出处
《计算机测量与控制》
北大核心
2013年第9期2503-2505,共3页
Computer Measurement &Control