2001•Acta Scientiarum Naturalium Universitatis SunyatseniRequires access

Fitting method of pseudo-polynomial for solving nonlinear parametric adjustment

陶华学, 宫秀军, 郭金运

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Abstract

The optimal condition and its geometrical characters of the least-square adjustment were proposed. Then the relation between the transformed surface and least-squares was discussed. Based on the above, a non-iterative method, called the fitting method of pseudo-polynomial, was derived in detail. The final least-squares solution can be determined with sufficient accuracy in a single step and is not attained by moving the initial point in the view of iteration. The accuracy of the solution relys wholly on the frequency of Taylor's series. The example verifies the correctness and validness of the method.

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The optimal condition and its geometrical characters of the least-square adjustment were proposed. Then the relation between the transformed surface and least-squares was discussed. Based on the above, a non-iterative method, called the fitting method of pseudo-polynomial, was derived in detail. The final least-squares solution can be determined with sufficient accuracy in a single step and is not attained by moving the initial point in the view of iteration. The accuracy of the solution relys wholly on the frequency of Taylor's series. The example verifies the correctness and validness of the method.

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Available abstract

The optimal condition and its geometrical characters of the least-square adjustment were proposed. Then the relation between the transformed surface and least-squares was discussed. Based on the above, a non-iterative method, called the fitting method of pseudo-polynomial, was derived in detail. The final least-squares solution can be determined with sufficient accuracy in a single step and is not attained by moving the initial point in the view of iteration. The accuracy of the solution relys wholly on the frequency of Taylor's series. The example verifies the correctness and validness of the method.

Key concepts: Mathematics, Correctness, Polynomial, Least-squares function approximation, Parametric statistics, Taylor series, Series (stratigraphy), Non-linear least squares

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