结果表明，在设计矩阵高度共线性时，用奇异值分解的迭代加细可以改进回归系数的估计。
Results show that iterative refinement using the SVD can improve regression coefficient estimates in the cases where the design matrix is highly collinear.
模型的基础上，泰勒级数的系数调整控制功能的迭代学习法律，学习增益矩阵，通过LMI优化设计。
Based on the model, the Taylor series coefficients of control function are adjusted by an iterative learning law and the learning gain matrix is designed via LMI optimization.
该新模型的海森矩阵是精确的常系数矩阵，在内点法迭代过程中只需要计算一次，从而缩短了每次迭代的计算时间。
The Hessian matrix of every function in this model is constant, so it will be calculated once in the entire optimal process based on interior point method, which speeds up each iteration.
计算结果表明，引入了属性矩阵和变超松弛系数的迭代算法能够更好地重建三维温度场。
The calculating results indicate that the 3-d temperature field can be reconstructed more accurately by the algorithm with property matrix and unfixed ultra-relaxation coefficient.
阻尼最小二乘法在较差的初值条件下能有效运行，并能克服系数矩阵奇异时的迭代困难。
Damped least-squares method can work successfully at a relatively poor initial value, and it can overcome the recurrence difficulty caused by the singular coefficient matrix.
该算法简化了投影系数矩阵的计算，调整了迭代算法逐线校正的迭代顺序。
This method proposes simplified computation of projection matrix and effectively adjusts the successive line iterative sequences.
该算法简化了投影系数矩阵的计算，调整了迭代算法逐线校正的迭代顺序。
This method proposes simplified computation of projection matrix and effectively adjusts the successive line iterative sequences.
应用推荐