| 1. | Time - varying system identification methods and convergence theorems
时变多变量系统多新息投影算法的均方收敛性 |
| 2. | Application of innovation grey theory to fault predication of uncertainty systems
新息灰理论在不确定性系统故障预测中的应用 |
| 3. | The title of xinxi marquis was given to fubo general ma yuan , so the name of the mountain
新息侯是伏波将军马援的封爵，所以山以伏波为名。 |
| 4. | Fubo mountain to the northeast of downtown guilin by the lijiang river has the xinxi marquis temple built during the tang dynasty 618 - 907
伏波山，位于市区东北，濒临漓江。唐代于山上建新息侯祠。 |
| 5. | According to the fact that the innovation has bias when the target is maneuvering , an adaptive filtering algorithm based on the innovation bias is given
并根据新息在目标机动时出现偏移的特点，提出了一种基于新息偏差的自适应滤波方法。 |
| 6. | According to the size of the new information from the kalman filter , the fuzzy controller is used to estimate the weigh coefficient of the filter kalman plus , and the using rate of new information has been increased
根据卡尔曼滤波中新息的大小，利用模糊控制器实时地估计卡尔曼滤波增益的权重系数，增加新息的利用率。 |
| 7. | 2 . the stable asymmetric power - garch model is applied to szsi and shci and stable law is fitted into the empirical distributions . the stability of standardized stable innovation is checked and the evaluation of prediction accuracy is performed
2 .对szsi以及shci建立了非对称稳定幂- garch模型，对其标准稳定新息进行了稳定分布拟合、稳定性检验以及预测精确性的实证检验。 |
| 8. | Based on online parameter estimation of the arma . innovation models , using the modern time series analysis method , the several self - tuning kalman tracking filters are presented , where the three different algorithms of the kalman tracking filter gains are used
基于arma新息模型参数的在线估计，应用现代时间序列分析的方法，提出了若干自校正kalman跟踪滤波器，其中，应用了求kalman跟踪滤波器稳态增益的三种不同算法。 |
| 9. | The deducing of the algorithms has very practical value in state estimation for systems under the complex environments . in the instance of complicated multi - channel system with multiplicative noise , the dissertation discusses the optimal estimation of state filtering and smoothing and the stochastic input signal with the technique of innovation and projection theorem of hilbert space . the main study of the dissertation is introduced as follows : 1 according to the practical requirement of complicated multi - channel system with multiplicative noise , the dissertation broadens rajasekaran filtering algorithm
本文针对复杂多通道带乘性噪声系统，应用新息的方法和hilbert空间的投影定理，对状态最优滤波和平滑估计、随机输入信号的最优估计等理论与应用方面的问题，进行了进一步的探讨，着重完成了以下工作：第一，根据复杂多通道乘性噪声系统问题的实际需要，推广了rajasekaran滤波算法。 |
| 10. | In operating process of systems , besides the external randoml disturbance from the , also influence also comes from inside as parameter changing , in order to cope with this two kinds of uncertainties , a minimization variance control strategy based on innovations is proposed rind the analytic solution of this suboptimal control is obtained in this paper
摘要系统在运行过程中，除了受到来自外界的随机干扰外，还受到了诸如内部参数引起的不确定性的影响，为对付这两种不确定性，采用双态控制方法，提出了基于新息的最小方差控制策略，获得了该次优控制律的解析解。 |
