自动化学报2012，Vol.38Issue(9)：1538-1543,6.DOI:10.3724/SP.J.1004.2012.01538
自组织状态空间模型参数初始分布搜索算法
Initial Distribution Search Algorithm for Self-organizing State Space Model
摘要
Abstract
The self-organizing state space model provides an efficient approach to estimating unknown parameters in a nonlinear non-Gaussian state space model. However, a difficult problem is how to determinate the initial distributions of parameters for a self-organizing state space model. To address this problem, this paper proposes an algorithm to seek the initial distribution of parameters for a self-organizing state space model. The proposed algorithm is based on an efficient evolutionary computation model which has global search capability. It makes the initial distribution of parameters close to the true parameter situation. The results of numerical experiments show the effectiveness of the proposed algorithm.关键词
自组织状态空间模型/粒子滤波/参数估计/非线性/非高斯Key words
Self-organizing state space model, particle filter,parameter estimation, nonlinear, non-Gaussian引用本文复制引用
甘敏,彭辉,黄云志,董学平..自组织状态空间模型参数初始分布搜索算法[J].自动化学报,2012,38(9):1538-1543,6.基金项目
国家国际科技合作计划(2011DFA10440),国家自然科学基金(70921001,61203106,71271215,51007016,60974022),湖南省科技厅国际合作重点项目(2009WK2009),中央高校基本科研业务费专项资金(2010HGBZ0597, 2011HGQC0995)资助 （2011DFA10440）
