| 1. | Minimum variance control based on nonlinear t - s fuzzy model
模糊模型的随机最小方差控制 |
| 2. | This algorithm is optimal in the sense of linear minimum - variance
该算法在线性最小方差意义下是最优的。 |
| 3. | Design of identification experiment signal for minimum variance control
基于最小方差控制的闭环辨识信号设计 |
| 4. | Minimum variance unbiased estimator
最小方差非偏估计 |
| 5. | Improving methods to calculate estimator minimum variance of the finite population mean
总体均值估计量最小方差的改进 |
| 6. | Minimum variance estimator
最小方差估计量 |
| 7. | Minimum variance estimation
最小方差估计 |
| 8. | All the proposed algorithms in this dissertation are optimal in the linear minimum - variance
本文所说最优均是建立在线性最小方差意义上的。 |
| 9. | A flow pattern identification method is proposed based on the least standard criterion
基于最小方差预测准则，提出水平管油气两相流流型辨识方法。 |
| 10. | Kalman filter is the best estimate under the linear and unprejudiced least mean square error rule
卡尔曼滤波是线性无偏最小方差准则下的最优估计。 |
