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Application of Iterative Calculation of Matrix for Solving Ill-posed Problems

机译:矩阵迭代计算在不适定问题求解中的应用

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The parameter estimations are unstable when the determinant of the coefficient matrix of the normal equation is closed to 0 in least-squares estimation. The deviation of estimator is too great because of rounding error of calculator and it is hard to get the precise inverse of the coefficient matrix. A matrix function which is matrix power series was introduced in proposed method based on ridge estimation. The matrix function is convergent to the normal equation coefficient matrix inverse and can be calculated through iterative calculation of matrix. Then the accuracy of the matrix inverse is improved and the estimations are robust. Three methods which are least-squares estimation, ridge estimation and iterative calculation were investigated. The second one is a biased estimation and it is difficult to get the appropriate ridge parameter, the third one is infinite times of calculation. The Theoretical analysis and computer simulation results show that the iterative calculation is precise and effective.
机译:当正态方程的系数矩阵的行列式在最小二乘估计中接近于0时,参数估计不稳定。由于计算器的舍入误差,估计量的偏差太大,难以获得系数矩阵的精确逆。提出了一种基于岭估计的矩阵函数,即矩阵幂级数。矩阵函数收敛于法线方程系数矩阵逆,并且可以通过矩阵的迭代计算来计算。然后提高了矩阵求逆的精度,并且估计是鲁棒的。研究了最小二乘估计,岭估计和迭代计算三种方法。第二个是有偏估计,很难获得适当的岭参数,第三个是计算的无限次。理论分析和计算机仿真结果表明,迭代计算是准确有效的。

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