An Adaptive Smoothing Method for Sensor Noise in Augmented Reality Applications on Smartphones

2012 ◽  
pp. 209-218 ◽  
Author(s):  
Rifat Ozcan ◽  
Fatih Orhan ◽  
M. Fatih Demirci ◽  
Osman Abul
Keyword(s):  
Augmented Reality ◽  
Smoothing Method ◽  
Sensor Noise ◽  
Adaptive Smoothing

scholarly journals Adaptive Smoothing Method For Computer Derivation of K-Indices

1991 ◽  
Vol 104 (1) ◽  
pp. 85-93 ◽  
Author(s):  
Krzysztof Nowożyński ◽  
Tomasz Ernst ◽  
Jerzy Jankowski
Keyword(s):  
Smoothing Method ◽  
Adaptive Smoothing

An Adaptive Smoothing Method for Continuous Minimax Problems

2015 ◽  
Vol 32 (01) ◽  
pp. 1540001
Author(s):  
Hongxia Yin
Keyword(s):  
Minimax Problems ◽  
Minimax Problem ◽  
Descent Method ◽  
Smoothing Parameter ◽  
Smoothing Method ◽  
Steepest Descent Method ◽  
Adaptive Smoothing ◽  
Ill Conditioning ◽  
Quasi Newton ◽  
Continuous Minimax

A simple and implementable two-loop smoothing method for semi-infinite minimax problem is given with the discretization parameter and the smoothing parameter being updated adaptively. We prove the global convergence of the algorithm when the steepest descent method or a BFGS type quasi-Newton method is applied to the smooth subproblems. The strategy for updating the smoothing parameter can not only guarantee the convergence of the algorithm but also considerably reduce the ill-conditioning caused by increasing the value of the smoothing parameter. Numerical tests show that the algorithm is robust and effective.

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