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This paper deals with the problem of speech enhancement when a
corrupted speech signal with an additive colored noise is the only
information available for processing. Kalman filtering is known as
an effective speech enhancement technique, in w
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This paper deals with the problem of speech enhancement when
only a corrupted speech signal is available for processing. Kalman
filtering is known as an effective speech enhancement technique,
in which speech signal is usually modeled as autore
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将非平稳时间序列的状态空间建模方法用于陀螺过渡过程的分析.基于平滑先验约束的概念，使用卡尔曼滤波和赤池的AIC方法拟合全局模型，得到陀螺漂移模型的若干数值结果并用于陀螺系统分析.由于观测序列的趋势项、不规则分量可同时建模，因此比分别建模在统计上更加准确有效.-Will be non-stationary time series state space modeling method for the analysis of the transition process gyro. Priori s
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kalman filter for state space model using Gaussian distribution
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卡尔曼滤波是一种数据处理方法，它是一种线性最小方差无偏估计准则，基于系统
状态估计和当前观测，通过引入状态空间而获得的新的状态估计.本篇论文陈述了卡尔曼滤
波的基本思路和算法；并通过仿真，显示卡尔曼滤波的功能，以及如何用它来跟踪方向确定、速度恒定的飞行器。-Kalman filter is a data processing method, which is a linear minimum variance unbiased estimation criteria, based on
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发散的一个新的Rauch-Tung-Striebel形式容积卡尔曼平滑了非线性状态空间模型采用求容积法为最优平滑转换-A new form of Rauch-Tung-Striebel volume divergence Kalman smoother nonlinear state space model using the volumetric method for seeking the optimal smooth transition
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(C-UKF)利用共识协议并将它应用于最优滤波器的非线性状态空间模型-Nonlinear state space model (C-UKF) and applies it to take advantage of the consensus agreement of the optimal filter
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kalman filter main routine can be used to DSGE model and state space model
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