Efficient algorithms of clustering adaptive nonlinear filters

Lainiotis D.G.; Papaparaskeva P.

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Efficient algorithms of clustering adaptive nonlinear filters

机译：聚类自适应非线性滤波器的高效算法

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This paper proposes a new class of efficient adaptive nonlinear filters whose estimation error performance (in a minimum mean square sense) is superior to that of competing approximate nonlinear filters, e.g., the well-known extended Kalman filter (EKF). The proposed filters include as special cases both the EKF and previously proposed partitioning filters. The new methodology performs an adaptive selection of appropriate reference points for linearization from an ensemble of generated trajectories that have been processed and clustered accordingly to span the whole state space of the desired signal. Through a series of simulation examples, the approach is shown significantly superior to the classical EKF with comparable computational burden

机译：本文提出了一种新型的高效自适应非线性滤波器，其估计误差性能（在最小均方意义上）优于竞争性近似非线性滤波器，例如众所周知的扩展卡尔曼滤波器（EKF）。提议的过滤器包括EKF和以前提议的分区过滤器作为特殊情况。新的方法从生成的轨迹集合中进行了适当的参考点的自适应选择，以进行线性化，这些轨迹已经过处理和聚类，从而跨越了所需信号的整个状态空间。通过一系列的仿真示例，该方法在计算负担上明显优于传统的EKF。

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《IEEE Transactions on Automatic Control》 |1999年第7期|p.1454-1459|共6页
作者
Lainiotis D.G.; Papaparaskeva P.;
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正文语种 eng
中图分类自动化系统;
关键词
Kalman filters; adaptive filters; filtering theory; linearisation techniques; nonlinear filters; nonlinear systems; state estimation; state-space methods; adaptive filters; clustering; extended Kalman filter; linearization; nonlinear filters; nonlinear systems; partit;

机译：卡尔曼滤波器;自适应滤波器;滤波理论;线性化技术;非线性滤波器;非线性系统;状态估计;状态空间方法;自适应滤波器;聚类;扩展卡尔曼滤波器;线性化;非线性滤波器;非线性系统;分区;

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专利

1. Efficient algorithms of clustering adaptive nonlinear filters [J] . Lainiotis D.G., Papaparaskeva P. IEEE Transactions on Automatic Control . 1999,第7期

机译：聚类自适应非线性滤波器的高效算法
2. Efficient training of neural nets for nonlinear adaptive filtering using a recursive Levenberg-Marquardt algorithm [J] . Ngia L.S.H., Sjoberg J. IEEE Transactions on Signal Processing . 2000,第7期

机译：使用递推Levenberg-Marquardt算法对神经网络进行非线性自适应滤波的有效训练
3. Transient Analysis of Complex-Domain Adaptive Threshold Nonlinear Algorithm (c-ATNA) for Adaptive Filters in Applications to Digital QAM Systems [J] . Shinichi KOIKE IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences . 2006,第2期

机译：用于数字QAM系统的自适应滤波器复域自适应阈值非线性算法（c-ATNA）的瞬态分析
4. Exploiting Signal Nongaussianity and Nonlinearity for Performance Assessment of Adaptive Filtering Algorithms: Qualitative Performance of Kalman Filter [C] . Chen Mo, Gautama Temujin, Obradovic Dragan, Nonlinear Statistical Signal Processing Workshop . 2007

机译：利用信号非岩性和非线性，用于适应性滤波算法的性能评估：卡尔曼滤波器的定性表现
5. Convergence analysis for efficient adaptive digital filtering algorithms and structures. [D] . Cho, Sung Ho. 1989

机译：用于高效自适应数字滤波算法和结构的收敛性分析。
6. Integrated Navigation System Design for Micro Planetary Rovers: Comparison of Absolute Heading Estimation Algorithms and Nonlinear Filtering [O] . Muhammad Ilyas, Beomjin Hong, Kuk Cho, 2016

机译：微型行星漫游车综合导航系统设计：绝对航向估计算法与非线性滤波的比较
7. A Normalized Gradient Descent Algorithm for Nonlinear Adaptive Filters Using a Gradient Adaptive Step Size [O] . Danilo P. M, Andrew I. Hanna, Moe Razaz 2016

机译：基于梯度自适应步长的非线性自适应滤波器的归一化梯度下降算法
8. Analysis of the Howells-Applebaum Algorithm in the Presence of Moving Interference. The Use of Lattice Filters in Adaptive Array Processors. Stability Analysis of LMS Adaptive Filters. Adaptive Array Processors with Moving Interference. [R] . Tuteur, F. B. 1982

机译：移动干扰下的Howells-applebaum算法分析。格子滤波器在自适应阵列处理器中的应用。 Lms自适应滤波器的稳定性分析。具有移动干扰的自适应阵列处理器。

Efficient algorithms of clustering adaptive nonlinear filters

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