1) Auxiliary variable particle filtering
辅助变量粒子滤波
2) auxiliary particle filter
辅助粒子滤波
1.
Combining multiple model theory and auxiliary particle filter algorithm,a new maneuvering target tracking algorithm called MMAPF is presented in the paper.
文中将多模型理论和辅助粒子滤波算法相结合,提出了一种新的机动目标跟踪算法——MM APF。
2.
The paper combines multiple model theory and auxiliary particle filter algorithm,and presents a new maneuvering target tracking algorithm called MMAPF(multi-model auxiliary particle filte.
文中将多模型理论和辅助粒子滤波算法相结合,提出了一种新的杂波环境下机动目标跟踪算法——多模型辅助粒子滤波算法(MMAPF)。
3.
Therefore,a new method——auxiliary particle filter(APF) is presented in which an assigned variable is brought and the weigh.
为此,本文引入一个辅助变量,利用一种新的使用二次加权操作的粒子滤波算法———辅助粒子滤波算法来对采样重要性重抽样算法进行改进。
3) auxiliary particle filtering
辅助粒子滤波
1.
Aiming at the computational complexity of particle filtering in blind multi-user detection,a new fast algorithm for blind multi-user detection based on auxiliary particle filtering is developed.
针对粒子滤波在盲多用户检测中计算复杂的问题,构建了一种低复杂度的辅助粒子滤波盲多用户检测快速算法。
2.
A sequential auxiliary particle filtering(SAPF) method is proposed to identify a non-stationary dynamic system with abrupt changes of system parameters.
提出一种非平稳动力系统突变参数识别的序贯辅助粒子滤波方法(SAPF方法)。
4) auxiliary kernel particle filter
辅助核粒子滤波
5) Auxiliary Marginal Particle Filter(AMPF)
辅助边缘粒子滤波器(AMPF)
6) auxiliary vector filtering
辅助向量滤波
1.
On the background of joint space-time anti-jammer processing for GPS receiver,multistage Wiener filter-ing(MWF)algorithm and auxiliary vector filtering(AVF)algorithm was deeply analyzed as two typical multistage itera-tive rank-reduced method in this article and their immanent relationship was pointed out.
深入分析了多级维纳滤波(MWF)和辅助向量滤波(AVF)两种典型的多步迭代降维方法,将其统一到同一框架内,并在此基础上给出一种基于数据域前向递推和后向迭代的改进多步迭代降维方法。
补充资料：辅助变量法
分子式：
CAS号：
性质：是针对最小二乘法的缺陷(比如将系统干扰假设为白色噪声，而实际是有色噪声)提出的一种改进方法，其关键在于如何构造辅助变量矩阵，它能较为有效地处理有色噪声的情形。
CAS号：
性质：是针对最小二乘法的缺陷(比如将系统干扰假设为白色噪声，而实际是有色噪声)提出的一种改进方法，其关键在于如何构造辅助变量矩阵，它能较为有效地处理有色噪声的情形。
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
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