| 1. | Simplified gauss - markov estimate with singular noise variance
估计在噪声方差矩阵不可逆时的化简 |
| 2. | Estimation of covariance matrices
协方差矩阵的估计 |
| 3. | Covariance matrix estimation
协方差矩阵估计 |
| 4. | Based on the constant velocity model , the principle of how to adjust the process noise covariance matrix q is analyzed
以常速模型为基础，分析了根据机动输入来调整过程噪声协方差矩阵q的原则。 |
| 5. | An advantage of this method is that it can be applied when the covariance matrix of the invested projects is positive semi - definite
该方法的优点在于能够处理各投资项目之间的协方差矩阵为半正定的情形。 |
| 6. | By using the optimized covariance matrices to optimize the new regularized discriminant analysis ( rda ) , the correct classification rate is higher than that by the old rda
利用优化的协方差矩阵对正则化判别分析方法进行优化，其模式分类正确率有显著提高。 |
| 7. | We analyses the different result of pca by using autocorrelation matrix and covariance matrix , and point out that the express of pca is different but the error are the same
分析了用协方差矩阵和自相关矩阵得出的pca表达是不同的，但是两者的误差是相同的。 |
| 8. | In this paper , an improvement is made through selecting a group of normal orthogonal vectors in feature subspace , to generate large amount of virtual training samples
摘要在模式特征子空间中选取一组标准正交向量，使用这组向量可以生成大量的虚拟训练样本，从而实现对协方差矩阵的优化。 |
| 9. | The main idea is to make full use of the decorrelation of two complex - valued vectors in generating independent components by non linear decorrelation
结合非正则复向量的协方差矩阵和伪协方差矩阵构造出了新的代价函数，进而提出新算法，通过复非线性不相关，从混合信号中提取出复值独立分量。 |
| 10. | A sub - optimal kalman filter is presented in chapter 3 , and the relative error covariance matrix ( recm ) is introduced to evaluate the performance of the fusion process ; 3
给出一种多传感器分布式次优kalman滤波器，并以相对误差协方差矩阵作为量化指标，对该滤波器的融合效果进行评估； 3 |
