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fuzzy-kalman
- 一种模糊卡尔曼滤波器的设计- One kind of fuzzy kalman filter design
ga-fuzzy-kalman
- 基于遗传算法的模糊卡尔曼滤波器-Fuzzy kalman filter based on inheritance algorithmic.
kalman_filter
- hybird ga , fuzzy and kalman filter algothomns
altitude
- 无人机高度基于matlab卡尔曼滤波程序 数据融合-UAV height matlab-based Kalman filter data fusion procedure
kalmanfuzzy
- 基于T-s模糊模型用于估计非线性系统的状态的kalman滤波器。-Ts-based fuzzy model used to estimate the state of nonlinear systems kalman filter.
fuzzy_kalman
- 3片关于fuzzy kalman filter的文章，较全面的说明了其原理-3 on fuzzy kalman filter the articles, a more comprehensive descr iption of its principle
kalmanfuzzy
- KALMAN FILTERING FOR FUZZY DYNAMIC SYSTEMS
AFuzzyAdaptiveTrackingAlgorithmBasedonCurrentStati
- 基于“当前”统计模型的模糊自适应跟踪算法 我存的一篇论文，拿来与大家共享-Current statistical model needs to pre-define the value of maximum accelerations of maneuvering targets.So it may be difficult to meet all maneuvering conditions.The Fuzzy inference combined with Current stati
FuzzyModel
- Fuzzy model for kalman filter
Kalman
- kalman filter using fuzzy logic
mohusuanfadelunwen
- 关于模糊控制与卡尔曼滤波结合的相关论文，包括模糊控制，模糊pid-Kalman filter on the combination of fuzzy control and the related papers, including fuzzy control, fuzzy pid, etc.
Achieving_integrity_in_an_INS_GPS_navigation_loop_
- 本文主要介绍了用模糊自适应卡尔曼滤波技术实现惯导和GPS的数据融合。-This paper presents a fuzzy adaptive Kalman filter technology for inertial navigation and GPS-data fusion.
jiyukaermanyundongmoxingmohutuxianghuifujishudeyan
- 基于卡尔曼运动模型模糊图像恢复技术的研究-Kalman Motion Model Based on Fuzzy Image Restoration Technique
Kalman
- 基于卡尔曼运动模型模糊图像恢复技术研究, 基于卡尔曼运动模型模糊图像恢复技术研究-Kalman Motion Model Based on Fuzzy Image Restoration Techniques
Fuzzy-Kalman-filter-implementation
- 利用模糊卡尔曼滤波器实现航空航天器的遥测遥控，在测控领域具有重要的应用价值。-Fuzzy Kalman filter implementation of aerospace remote sensing and control, measurement and control have important application value.
Kalman---Fuzzy-Extended
- Kalman - Fuzzy Extended
03thesis
- A Fuzzy-Kalman Filtering Strategy for State Estimation
barbosa2016
- Linear Quadratic Gaussian (LQR) controller and Kalman Filter (KF) both are robust when acting separately, but this property is lost if using them together.