• The KIPS Transactions:PartB
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• v.9B no.3
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• pp.271-276
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• 2002

The test statistic in ANOVA tests has a single or doubly noncentral F distribution and the noncentral F distribution is applied to the calculation of the power functions of tests of general linear hypotheses. Although various approximations of noncentral F distribution are suggested, they are troublesome to compute. In this paper, the calculation of noncentral F distribution is applied to the neural network theory, to solve the computation problem. The neural network consists of the multi-layer perceptron structure and learning process has the algorithm of the backpropagation. Using fables and figs, comparisons are made between the results obtained by neural network theory and the Patnaik's values. Regarding of accuracy and calculation, the results by neural network are efficient than the Patnaik's values.

• Journal of the Korea Society of Computer and Information
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• v.1 no.1
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• pp.83-94
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• 1996

The test statistic in ANOVA tests has a single or doubly noncentral F distribution and the noncentral F distribution is applied to the calculation of the power functions of tests of general linear hypotheses. In this paper. the evaluation of the cumulative function of the single noncentral F distribution is applied to the neural network theory. The neural network consists of the multi-layer perceptron structure and learning process has the algorithm of the backpropagation. Numerical comparisons are made between the results obtained by neural network theory and the Patnaik's values.