A gradient-based eigenspace approach to dealing with occlusions and non-Gaussian noise

2003 ◽  
Author(s):  
H. Wildenauer ◽  
T. Melzer ◽  
H. Bischof
Keyword(s):  
Gaussian Noise ◽  
Gradient Based ◽  
Non Gaussian

scholarly journals Robust Variable Selection and Estimation Based on Kernel Modal Regression

Entropy ◽  
2019 ◽  
Vol 21 (4) ◽  
pp. 403 ◽  
Author(s):  
Changying Guo ◽  
Biqin Song ◽  
Yingjie Wang ◽  
Hong Chen ◽  
Huijuan Xiong
Keyword(s):  
Variable Selection ◽  
Gaussian Noise ◽  
Free Variable ◽  
Noise Condition ◽  
New Model ◽  
Information Theoretic Learning ◽  
Model Free ◽  
Modal Regression ◽  
Gradient Based ◽  
Non Gaussian

Model-free variable selection has attracted increasing interest recently due to its flexibility in algorithmic design and outstanding performance in real-world applications. However, most of the existing statistical methods are formulated under the mean square error (MSE) criterion, and susceptible to non-Gaussian noise and outliers. As the MSE criterion requires the data to satisfy Gaussian noise condition, it potentially hampers the effectiveness of model-free methods in complex circumstances. To circumvent this issue, we present a new model-free variable selection algorithm by integrating kernel modal regression and gradient-based variable identification together. The derived modal regression estimator is related closely to information theoretic learning under the maximum correntropy criterion, and assures algorithmic robustness to complex noise by replacing learning of the conditional mean with the conditional mode. The gradient information of estimator offers a model-free metric to screen the key variables. In theory, we investigate the theoretical foundations of our new model on generalization-bound and variable selection consistency. In applications, the effectiveness of the proposed method is verified by data experiments.

STATEMENT OF THE PROBLEM ON SYNTHESIS OF OPTIMAL EVALUATION OF SIGNAL PARAMETERS IN NON-GAUSSIAN NOISE

2012 ◽  
Vol 71 (17) ◽  
pp. 1541-1555
Author(s):  
V. A. Baranov ◽  
S. V. Baranov ◽  
A. V. Nozdrachev ◽  
A. A. Rogov
Keyword(s):  
Gaussian Noise ◽  
Signal Parameters ◽  
Non Gaussian ◽  
Optimal Evaluation

NONPARAMETRIC DECODING OF BLOCK CODES IN CHANNELS WITH NON-GAUSSIAN NOISE

2013 ◽  
Vol 72 (11) ◽  
pp. 1029-1038
Author(s):  
M. Yu. Konyshev ◽  
S. V. Shinakov ◽  
A. V. Pankratov ◽  
S. V. Baranov
Keyword(s):  
Gaussian Noise ◽  
Block Codes ◽  
Non Gaussian

Wavelet threshold algorithm analysis under non-Gaussian noise background

2013 ◽  
Vol 32 (9) ◽  
pp. 2445-2447
Author(s):  
Qing-hua LI ◽  
Dalabaev Senbai ◽  
Xin-jian QIU ◽  
Chang LIAO ◽  
Quan-fu SUN
Keyword(s):  
Gaussian Noise ◽  
Algorithm Analysis ◽  
Noise Background ◽  
Threshold Algorithm ◽  
Non Gaussian
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