Amortized Complexity Analysis for Red-Black Trees and Splay Trees

2018 ◽  
Author(s):  
Isha Ashish Bahendwar ◽  
RuchitPurshottam Bhardwaj ◽  
S. G. Mundada
Keyword(s):  
Complexity Analysis ◽  
Amortized Complexity

scholarly journals Amortized Complexity Analysis for Red-Black Trees and Splay Trees

2018 ◽  
Vol 6 (6) ◽  
pp. 121-128
Author(s):  
Isha Ashish Bahendwar ◽  
Ruchit Purshottam Bhardwaj ◽  
Prof. S.G. Mundada
Keyword(s):  
Complexity Analysis ◽  
Amortized Complexity

Centered error entropy Kalman filter with application to satellite attitude determination

2021 ◽  
pp. 014233122110198
Author(s):  
Baojian Yang ◽  
Lu Cao ◽  
Dechao Ran ◽  
Bing Xiao
Keyword(s):  
Kalman Filter ◽  
Gaussian Noise ◽  
Attitude Determination ◽  
Complexity Analysis ◽  
Iteration Algorithm ◽  
Robust Algorithms ◽  
Convergence Conditions ◽  
Satellite Attitude ◽  
Heavy Tailed ◽  
Non Gaussian

Due to unavoidable factors, heavy-tailed noise appears in satellite attitude estimation. Traditional Kalman filter is prone to performance degradation and even filtering divergence when facing non-Gaussian noise. The existing robust algorithms have limited accuracy. To improve the attitude determination accuracy under non-Gaussian noise, we use the centered error entropy (CEE) criterion to derive a new filter named centered error entropy Kalman filter (CEEKF). CEEKF is formed by maximizing the CEE cost function. In the CEEKF algorithm, the prior state values are transmitted the same as the classical Kalman filter, and the posterior states are calculated by the fixed-point iteration method. The CEE EKF (CEE-EKF) algorithm is also derived to improve filtering accuracy in the case of the nonlinear system. We also give the convergence conditions of the iteration algorithm and the computational complexity analysis of CEEKF. The results of the two simulation examples validate the robustness of the algorithm we presented.

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