本文简述了它的工作原理，并在前人分析的基础上提出了滤波器动态概率变换特性的概念。
In this paper, the basic principle of this DPLL and the concept of the dynamic probability transformation characteristic are proposed.
为了更有效地利用图像的局部特征恢复被噪声感染的图像，基于图像局部纹理方向概率统计模型，提出一种针对混合噪声的非线性滤波算法。
In order to more effectively make use of local features to restore the noise-infected image, a nonlinear filtering algorithm based on local texture direction probability statistic model was proposed.
利用概率滤波可得分解后的地震图，从图中可以直接得到震相到时。
The decomposed seismogram is obtained by using probability filtering, the arrived time can be find out from it directly.
为了提高红外图像序列中弱小目标的信噪比和检测概率，同时考虑检测算法实时性，提出了一种新的基于空时域滤波的小目标检测方法。
To improve the Signal-to-noise Ratio(SNR) and detecting probability of small target in infrared image sequences, a novel method of target detection based on spatial-temporal filtering is proposed.
模板的元素取自目标特征值的概率，通过48个卡尔曼滤波器可以跟踪所有特征值的概率变化。
The element of template is probability of eigenvalue of target. These probability are acquire by a kalman filter group which had 48 kalman filters.
以声表面波滤波器组为核心的信道化接收机，可以实现对雷达信号的宽频的信道化接收和100%的截获概率。
Channelized receiving of wide band radar signal and 100 percent of probability of intercept can be realized by channelized receiver based on SAW filter Banks.
这是一个实现全概率接收的程序，基于多相滤波器组成的信道化接收机。
This is a realization of the probability of receiving the whole process, based on the polyphase filter composed of channelized receiver.
在噪声去除阶段将随机游走的概念引入到向量排序中，通过最大化中心象素与周围象素的转移概率计算滤波器的输出。
It introduces random walk concept into vector ordering and finds the output which maximizes transition probability from central pixel to its neighbors.
在滤波算法中，我们用一簇高斯厄米特滤波器(GHF)来产生重要性概率密度函数。
In the new algorithm, a bank of Gauss-Hermite filter (GHF) is used for generating the importance density function.
将改进的概率神经网络(PNN)用于奇异摄动系统的实时状态估计，注重针对系统快变部分的滤波。
Probabilistic Neural Networks (PNN) is improved and used on line to estimate the states of singular perturbed systems, especially to the fast states of the systems.
针对这一问题，首先分析了复信号多相滤波器无盲区算法及其数学模型，实现信号的全概率捕获。
A design method and structural implementation of wideband digital channelized receiver based on poly-phase filters is introduced.
概率跟踪卡尔曼滤波和粒子滤波是这类方法的典型代表。
Kalman filter and particle filter is a typical representative of the probability tracking methods.
该方法以球坐标系中三通道解耦自适应卡尔曼滤波为基础，结合最近邻（NN）方法或概率数据关联滤波（PDAF）方法实现杂波中的机动目标跟踪。
Based on adaptive Kalman filter in polar coordinates, the algorithm was implemented with NN method and PDAF to fuse sensors in clutter.
传统的粒子滤波通常采用系统转移概率作为建议分布，但传统的建议分布选取方法由于没有考虑新的观测信息，因此不能产生准确的估计值。
The traditional particle filter USES system transition probability as the proposal distribution without considering the new observing information; therefore, they cannot give accurate estimation.
最后，使得粒子的分布更加接近状态的后验概率密度，最大化地实现其滤波性能。
Finally, the particle distribution approaches to the station posterior distribution and the maximum filtering performance is achieved.
用一个递归滤波器估计回波平均功率，并计算真实回波和欺骗回波的检测概率，用于相关计算和欺骗终止判断。
The average power of both true skin and deception echo is estimated recursively to calculate the detection probabilities which are used in 2D assignment and RGPO breaking-off judgment.
提出了一种基于杂波模型的极化自适应恒虚警检测算法，该算法比极化自适应匹配滤波器算法有更小的估计损失，并推导出了虚警概率表达式。
A model - based polarimetric adaptive CFAR detection algorithm is derived that has a lower estimation loss. A theoretical expression is derived for constant false alarm rate of the proposed algorithm.
提出了一种基于杂波模型的极化自适应恒虚警检测算法，该算法比极化自适应匹配滤波器算法有更小的估计损失，并推导出了虚警概率表达式。
A model - based polarimetric adaptive CFAR detection algorithm is derived that has a lower estimation loss. A theoretical expression is derived for constant false alarm rate of the proposed algorithm.
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