DocumentCode :
45311
Title :
Stochastic computation of moments, mean, variance, skewness and kurtosis
Author :
Georgiou, G.M. ; Voigt, K.
Author_Institution :
Sch. of Comput. Sci. & Eng., California State Univ., San Bernardino, CA, USA
Volume :
51
Issue :
9
fYear :
2015
fDate :
4 30 2015
Firstpage :
673
Lastpage :
674
Abstract :
Stochastic computation of statistical moments and related quantities, such as the mean, variance, skewness and kurtosis, is performed with simple neural networks. The computed quantities can be used to estimate the parameters of input data probability distributions, gauge the normality of data, add useful features to the inputs, preprocess data and for other applications. Such neural networks can be embedded in larger ones that perform signal processing or pattern recognition tasks. Convergence to the correct values is demonstrated with experiments.
Keywords :
mathematics computing; neural nets; statistical analysis; data gauge normality; input data probability distributions; neural networks; pattern recognition task; signal processing task; statistical kurtosis; statistical mean; statistical moments; statistical skewness; statistical variance; stochastic computation;
fLanguage :
English
Journal_Title :
Electronics Letters
Publisher :
iet
ISSN :
0013-5194
Type :
jour
DOI :
10.1049/el.2015.0066
Filename :
7095681
Link To Document :
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