Based on building up a model of echo canceller, the convergence of gradient-type stochastic adjustment algorithm of an adaptive filter under the mean-squared error criterion is discussed.
在建立回波抵消器模型的基础上，按最小均方误差准则，导出了自适应滤波器抽头的统计梯度算法和抽头调节的收敛公式。
Using white noise to drive shaping filter, the interference model of wave is acquired on the basis of stable stochastic process theory, and the simulation results are satisfactory.
根据平稳随机过程理论，利用白噪声驱动成形滤波器，获得海浪的干扰模型，并得到了令人满意的仿真结果。
Using the methods of time series spectral analysis and Kalman filter, this article discussed the additive problems of two stochastic processes, mainly Auto Regression Moving Average (ARMA) processes.
本文利用时间序列谱分析和卡尔曼滤波的方法讨论了两个随机过程，主要是自回归滑动平均(ARMA)过程，的叠加问题。
By using the forming filter and EKF, the precision of states estimation is increased and a effective estimation of stochastic sea interference is performed.
通过引入成型滤波器，采用EKF，提高了状态估计的精度，实现对随机海浪扰动力和力矩的估计。
An extended Kalman filter with adaptive gain was used to build a miniature attitude and heading reference system based on stochastic model.
利用改进的自适应增益卡尔曼滤波器在随机模式下建立一个小型姿态确定系统。
Kalman filter used in linear discrete stochastic system has good convergence and the ability to remove high frequency noises.
卡尔曼滤波用于线性离散随机系统具有非常好的收敛性和滤除高频噪声的能力。
An inverse stochastic boundary element method for prediction of contact stress is presented by combining improved filter algorithm with stochastic boundary element method.
将改进的滤波算法和随机边界元法结合，提出了用于预测接触应力的逆随机边界元法。
Based on the extended Kalman filter, an identification method on physical parameters of bridge structures subjected to stochastic loads is proposed.
基于广义卡尔曼滤波提出了随机荷载作用下桥梁结构物理参数的识别方法。
A modified strong tracking Kalman filter (MSTKF) for linear stochastic systems is proposed.
针对线性随机系统提出了一种改进强跟踪卡尔曼滤波器(MSTKF)。
The optimal moving average filter for the linear stochastic controlled plant is developed from the viewpoint of the internal model of the deterministic disturbance.
从确定性干扰的内模观点导出了适用于线性随机受控对象的最优滑动滤波器。
In this paper, formulas are derived for the minimal order filter in a singular, linear time-invariant, continuous and stochastic system.
本文讨论了奇异线性定常连续随机系统最小阶滤波器的设计问题。
A self-adapting Kalman Filter based on the principle of stochastic approximatation is introduced in the paper. This filter provides an ideal means for the tracking of underwater noise source.
本文根据随机逼近原理提出了一种自适应卡尔曼滤波器，适用于被动声纳对水下噪声源的跟踪。
Based on decomposition and reconstruction of the signals by filter sets, the trend-signal is separated from stationary stochastic signals.
这种方法通过滤波器组将信号分解与重构，实现趋向性信号与零均值平稳随机信号的分离。
A filter algorithm of bayesian state estimation using piecewise constant was proposed for a nonlinear stochastic system with white noises.
针对具有高斯噪声的非线性随机系统状态估计问题，提出了一种基于分段常值的贝叶斯状态估计滤波算法。
According to the giving wave spectrum, the coefficient of nonlinear wave filter is gotten by the method of stochastic averaging.
应用随机平均法，根据所给定的波浪谱确定滤波器参数。
According to the giving wave spectrum, the coefficient of nonlinear wave filter is gotten by the method of stochastic averaging.
应用随机平均法，根据所给定的波浪谱确定滤波器参数。
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