用高斯-牛顿误差最小法将六维观测量转化为四元数，作为观测量的一部分，显著减少了直接使用EKF的计算量。
Gauss-Newton error minimization is used to transform six-dimentional reference vector to quaternion as a part of observations for EKF, which significantly reduces the computational requirement.
本文通过理论推导，证明在反应动力学常微分方程参数估值中所采用的拟线性化法在本质上仍然属于高斯—牛顿法的范畴。
This paper proves that the quasilinearization method for parameter estimation of ordinary differential equation in chemical reaction kinetics essentially belongs to the region of Gauss-Newton method.
该算法通过两步递 归最优化方法来实现 ，并采用改进的高斯—牛顿法来确保算法的快速收敛 性。
The EML registration is achieved by two step recursive optimization. The quick convergence is assured through the improved Gauss Newton algorithm.
结果表明合成算法优于单纯的遗传算法或高斯-牛顿法，在实践中有一定的应用价值。
The results showed that the practically mixed algorithm was better than simple GA or Gauss-Newton algorithm.
文中对用高斯·牛顿法拟合三参数和四参数极化曲线方程序求取电化学动力学参数提出了两种改进方法。
Based on the idea of curve fitting, the nonlinear least squares method (Gauss-Newton method) has been applied to estimate the complex parameters.
文中对用高斯·牛顿法拟合三参数和四参数极化曲线方程序求取电化学动力学参数提出了两种改进方法。
Based on the idea of curve fitting, the nonlinear least squares method (Gauss-Newton method) has been applied to estimate the complex parameters.
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