1,940 research outputs found
Policy Optimization of Finite-Horizon Kalman Filter with Unknown Noise Covariance
This paper is on learning the Kalman gain by policy optimization method.
Firstly, we reformulate the finite-horizon Kalman filter as a policy
optimization problem of the dual system. Secondly, we obtain the global linear
convergence of exact gradient descent method in the setting of known
parameters. Thirdly, the gradient estimation and stochastic gradient descent
method are proposed to solve the policy optimization problem, and further the
global linear convergence and sample complexity of stochastic gradient descent
are provided for the setting of unknown noise covariance matrices and known
model parameters
Outstanding supercapacitive properties of Mn-doped TiO2 micro/nanostructure porous film prepared by anodization method.
Mn-doped TiO2 micro/nanostructure porous film was prepared by anodizing a Ti-Mn alloy. The film annealed at 300 °C yields the highest areal capacitance of 1451.3 mF/cm(2) at a current density of 3 mA/cm(2) when used as a high-performance supercapacitor electrode. Areal capacitance retention is 63.7% when the current density increases from 3 to 20 mA/cm(2), and the capacitance retention is 88.1% after 5,000 cycles. The superior areal capacitance of the porous film is derived from the brush-like metal substrate, which could greatly increase the contact area, improve the charge transport ability at the oxide layer/metal substrate interface, and thereby significantly enhance the electrochemical activities toward high performance energy storage. Additionally, the effects of manganese content and specific surface area of the porous film on the supercapacitive performance were also investigated in this work
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