摘要
与D-S理论相比,DSmT可以很好地解决证据矛盾时的证据组合问题,但是DSmT在很多情况下主焦元mass函数难以收敛。在标准DSmT的框架下,将其融合后的mass函数进行重构,从而提出一种改进的DSmT,该算法的主焦元mass函数可以快速收敛。在进行二维飞机序列图像的目标类型识别中,该改进DSmT进行迭代运算,可使主焦元的mass值快速收敛到指定的阈值,以便完成准确的目标识别。
The Dezert-Smarandache Theory （DSmT） is more desirable than the D-S Theory in the case of solving conflicting evidence, However, the mass function of the main focal element is difficult to converge in many cases while applying DSmT. The new mass values were reconstructed to solve this problem. An improved DSmT was proposed so that the mass value of main element could quickly converge. Simulation results of target recognition based on 2D sequence images of airplanes demonstrate that the revised mass value of main focal element has better convergence to the desired threshold and consequently the task of target recognition is accomplished more precisely.
出处
《计算机应用》
CSCD
北大核心
2005年第9期2044-2046,共3页
journal of Computer Applications
基金
国家自然科学基金资助项目(60372085
60404011)
陕西省科学技术研究发展计划项目(2003K06-G15)
