If both of the input and output data in in-situ calibration contain have noises, the result will be a biased one when the traditional least squares method is used for parameter identification.
在原位标定输入输出观测数据均含有噪声的情况下，应用传统的最小二乘法进行参数辨识将会得到有偏的结果。
This paper presents new development of parameter identification for MIMO discrete stochastic linear systems with random parameters based on the least squares method.
本文讨论了参数估计和输出误差的收敛性，并给出了系统持续激励的一个充分条件。
The magnetization parameter is estimated by the least-squares parameter identification with the consideration of main flux saturation and the experimental data agree with the simulative results.
考虑主磁路饱和的同步电机激磁参数的估计值由最小二乘法参数辨识得到，实验数据与仿真结果基本吻合。
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