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QICID: 20794
Title: A Neural Network-Based Approach for Statistical Probability Distribution Recognition
Copyright: 2006, ASQ and Taylor & Francis Group, LLC
Author: Su, C.-T.; Chou, C.-J.
Organization: National Tsing Hwa University, Hsinchu, Taiwan
Subject: Goodness of fit,Neural networks,Probability function,Sample size,Statistical tests;
Series: Quality Engineering, Vol. 18, No. 3, July 2006, pp. 293-297
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Abstract: [This abstract is based on the authors' abstract.]Until recently, a nonparametric goodness of fit test has been used in probability distribution recognition, but this test cannot guarantee precise distribution recognition when only small data samples are available. In this study, two types of neural networks, backpropagation and learning vector quantization, are used for probability distribution recognition. Results demonstrate the proposed approach outperforms the traditional statistical approach.
Number of pages: 5
Price for ASQ Members: $5.00
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