计算机科学 ›› 2014, Vol. 41 ›› Issue (8): 289-292.doi: 10.11896/j.issn.1002-137X.2014.08.061
韩光,孙宁,李晓飞,赵春霞
HAN Guang,SUN Ning,LI Xiao-fei and ZHAO Chun-xia
摘要： 提出了一种基于改进的混合粒子群优化(particle swarm optimization,PSO)算法的高斯混合模型地形分类方法。高斯混合模型的求解通常是使用期望最大化算法(expectation maximization,EM),然而EM算法易陷入局部最优,收敛速度不稳定且对初值敏感。因此引入混合PSO算法,并对其进行了一系列改进。实验结果表明:改进后的算法较其它优化算法提高了全局搜索能力和收敛速度,利用该算法求解高斯混合模型可以提高参数估计的精度,并且在户外场景图像的地形分类实验中所提出的地形分类方法也表现优良。
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