Apparatus for and method of generating an approximation function

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364719, 364720, 364722, 364723, 395 21, G06F 102, G06F 738, G06E 100, G06E 300

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055196470

ABSTRACT:
An apparatus (5) for generating an approximation function based on first pairs ((X.sub.1, Y.sub.1) to (X.sub.6, Y.sub.6)) of values associating a dependent variable (Y.sub.1 to Y.sub.6) with an independent variable (X.sub.1 to X.sub.6), and for determining second pairs (X.sub.A, Y'.sub.A) of values of said variables in accordance with said approximation function. The apparatus comprises: a) first means (10) for iteratively determining at least one current linear regression function, for selecting that one of the current linear functions which produces the approximation of all the pairs of said series with minimal errors, and for coding the selected linear regression function with the aid of specific codes (p, q), and b) second means (17) for determining said second pairs (X.sub.A, Y'.sub.A) with the aid of said specific codes. The apparatus can also be used for calculating approximated values of mathematical functions, for example a in a neural network, or for determining a regression function forming an approximation to experimental measurement results, for example distributed measurements resulting from monitoring an industrial process. The invention also relates to a method of generating an approximation function.

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Lippmann, "An Introduction to Computing with Neural Nets", IEEE ASSP Magazine Apr. 1987, pp. 4-22.
Ishibuchi et al., "Regression Analysis with Interval Model by Neural Networks", 1991 IEEE International Joint Conference on Neural Networks, vol. 2, Nov. 18-21, 1991, pp. 1594-1599.

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