研究一类非因果系统的最小方差滤波与平滑。
In this paper, minimum variance filtering and smoothing algorithms of a class of non-causal systems are discussed.
卡尔曼滤波是一种线性最小方差状态估计，把它有效地结合阵列天线与多用户检测。
Kalman filter is a linear minimum variance state estimator, and it combined array antenna and multiuser detection effectively.
为了进一步改善波束形成器的降噪性能，文章提出了一种基于维纳滤波的线性约束最小方差波束形成器。
A new method of linearly constrained minimum variance beamforming that based on Wiener filter is proposed to improve its performance of noise reduction.
该波束形成器首先让信号经过维纳滤波器消除非相干噪声，而后经过经典的线性约束最小方差处理，最终达到较好的语音增强效果。
This kind of beamformer can eliminate incoherent noise when signals pass Wiener filter, then achieve a better speech-enhance effect by linear constraints minimum variance beamforming.
卡尔曼滤波，是线性、无偏、最小方差的实时递推滤波，是一种高效、优化的数据处理方法。
Kalman filter is a high efficiency, optimal data process method, which is a realtime recursive filter of linear, non-bias and least square.
卡尔曼滤波，是线性、无偏、最小方差的实时递推滤波，是一种高效、优化的数据处理方法。
Kalman filter is a high efficient, optimal data process method, which is a real time recursive filter based on linear, non-bias and least square approach.
利用射影理论，推导出了在线性最小方差意义下状态滤波器和白噪声滤波器。
Based on projection theory, the optimal filters for state and white noise are derived in the linear minimum variance sense.
采用最小方差理论和平均原理对自适应滤波算法进行分析，对信号中产生的延时和相移予以有效补偿。
By using minimum variance and average principle, the adaptive filtering algorithm is analyzed to effectively compensate the time-delay and phase shift that appear in signals.
采用最小方差理论和平均原理对自适应滤波算法进行分析，对信号中产生的延时和相移予以有效补偿。
By using minimum variance and average principle, the adaptive filtering algorithm is analyzed to effectively compensate the time-delay and phase shift that appear in signals.
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