在此基础上，建立了最小方差损失函数，并结合高斯·牛顿预测误差方法，提出了稳定的，高性能的，在线的复频率直接估计算法。
A cost function is presented, and by applying Gaussian-Newton type recursive prediction error based method, a stable and efficient online frequency estimation algorithm is derived.
为了提高复合双基地雷达系统对目标的定位精度，以及充分利用冗余信息，提出了基于高斯·牛顿算法的空间目标定位算法。
For improving targets location accuracy and fully utilizing redundant information in complex bistatic radar systems, a new target location algorithm based on Gauss-Newton iterative is proposed.
在多种常用的非线性局域优化算法中，高斯·牛顿算法具有较快的收敛速度。
In many usually used nonlinear local optimization algorithms, Gauss Newton's is of fast convergent speed.
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.
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.
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