Minimum variance unbiased FIR filter for discrete time-variant systems

Automatica ◽  
2015 ◽  
Vol 53 ◽  
pp. 355-361 ◽  
Author(s):  
Shunyi Zhao ◽  
Yuriy S. Shmaliy ◽  
Biao Huang ◽  
Fei Liu
Keyword(s):  
Discrete Time ◽  
Minimum Variance ◽  
Fir Filter ◽  
Unbiased Fir Filter

A receding horizon unbiased FIR filter for discrete-time state space models

Automatica ◽  
2002 ◽  
Vol 38 (3) ◽  
pp. 545-551 ◽  
Author(s):  
Wook Hyun Kwon ◽  
Pyung Soo Kim ◽  
Soo Hee Han
Keyword(s):  
State Space ◽  
Discrete Time ◽  
Fir Filter ◽  
State Space Models ◽  
Receding Horizon ◽  
Unbiased Fir Filter

Extended least square unbiased FIR filter for target tracking using the constant velocity motion model

2017 ◽  
Vol 15 (2) ◽  
pp. 947-951 ◽  
Author(s):  
Jung Min Pak ◽  
Pyung Soo Kim ◽  
Sung Hyun You ◽  
Sang Seol Lee ◽  
Moon Kyou Song
Keyword(s):  
Target Tracking ◽  
Constant Velocity ◽  
Fir Filter ◽  
Least Square ◽  
Motion Model ◽  
Unbiased Fir Filter ◽  
Velocity Motion

Calculation of Optimized Movement Trajectories for the Human Forearm

2013 ◽  
Vol 401-403 ◽  
pp. 1347-1352
Author(s):  
Li Li Yang
Keyword(s):  
Discrete Time ◽  
Linear Quadratic Regulator ◽  
Minimum Variance ◽  
Movement Trajectory ◽  
Linear Quadratic ◽  
Variance Model ◽  
Movement Trajectories ◽  
Human Forearm ◽  
Optimal Movement ◽  
Time Linear

Using the minimum variance model, optimal human forearm trajectories formation was investigated using a discrete time linear quadratic regulator. First, the continuous dynamics of the human forearm were established on the basis of the relation between muscle torque and neural control signal, and then we transferred the continuous system dynamics to discrete time notation. Finally we expressed the objective function of minimum variance model using a discrete time linear quadratic regulator and employed Riccati recursion to obtain the optimal movement trajectories of the human forearm. The results of example simulation show that the optimal movement trajectory of the forearm follows a smooth curve, and the speed curve of the hand is single peaked and bell shaped. These are in good agreement with the inherent kinematic properties of optimal movement, and therefore the method is effective for calculating the optimal movement trajectory of the human forearm.

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