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The Kalman filter is an efficient recursive filter that estimates the state of a linear dynamic system from a series of noisy measurements. It is used in a wide range of engineering applications from radar to computer vision, and is an important topi
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Adaptive Continuous-Time Linear
Quadratic Gaussian Control
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带有卡尔曼滤波器的线性二次高斯自适应算法-Linear quadratic Gaussian adaptive algorithm with the Kalman filter
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vb6.0编写的最小二乘法直线拟合、二次曲面拟合程序，线性方程组采用列主元高斯消去法。-vb6.0 prepared by the method of least squares fitting a straight line, the quadratic surface fitting procedure, linear equations using Gaussian elimination main-element.
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olve the deterministic finite-horizon optimal control problem with the iLQG (iterative Linear Quadratic Gaussian) or modified DDP (Differential Dynamic Programming) algorithm. Includes two demos, a linear control-constrained problem and a car-parking
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Linear quadratic gaussian for control a simulation aircraft pitch system
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Kalman Filter是一个高效的递归滤波器，它可以实现从一系列的噪声测量中，估 计动态系统的状态。广泛应用于包含Radar、计算机视觉在内的等工程应用领域，在控制理论和控制系统工程中也是一个非常重要的课题。连同线性均方规划，卡尔曼滤波器可以用于解决LQG(Linear-quadratic-Gaussian control)问题。卡尔曼滤波器，线性均方归化及线性均方高斯控制器，是大部分控制领域基础难题的主要解决途径。(Kalman Filter is an efficient recursi
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Linear Quadratic Gaussian (LQR) controller and Kalman Filter (KF) both are robust when acting separately, but this property is lost if using them together.
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