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