计算机工程与应用2011，Vol.47Issue(10)：110-112,223,4.DOI:10.3778/j.issn.1002-8331.2011.10.031
状态空间双线性系统的极大似然辨识
Maximum-likelihood identification of state-space bilinear systems
摘要
Abstract
Maximum likelihood identification is proposed for parameter estimation of state-space bilinear systems.The likelihood function conditioned on input-output series is constructed.Moreover,the parameter matrix is determined by the maximization of the likelihood function,and the modified Kalman filter suitable for state estimation of bilinear systems is presented.In addition, iterative parameter estimation algorithm for maximization of likelihood function is also given.Finally, numerical simulation is implemented and the results show the effectiveness of the proposed method.关键词
系统辨识/极大似然/双线性系统/状态空间模型Key words
system identification/maximum likelihood/bilinear system/state-space model.分类
数理科学引用本文复制引用
衷路生,樊晓平,杨辉,瞿志华,齐叶鹏,颜争..状态空间双线性系统的极大似然辨识[J].计算机工程与应用,2011,47(10):110-112,223,4.基金项目
国家自然科学基金(the National Natural Science Foundation of China under Grant No.60870010,No.60864004,No.60904049) （the National Natural Science Foundation of China under Grant No.60870010,No.60864004,No.60904049）
国家高技术研究发展计划(863)(the National High Technology Research and Development Program of China under Grant No.2008AA04Z129). （863）
