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a posteriori probability相关的网络例句

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与 a posteriori probability 相关的网络例句 [注:此内容来源于网络,仅供参考]

This algorithm does not need either a priori knowledge or a posteriori probability, and has convergence with excellent stability.

此算法无须先验知识或后验概率,具有良好的稳定收敛性。

In this algorithm, the direction-of-arrival is assumed to be a discrete random variable with a priori probability density function defined on a set of candidate points. Whether or not the secondary sample is required is based on the a posteriori probability distribution of a set of candidate point"s, which can be calculated from the array received signals. And then, the resulting beamformer is a weighted sum of the beamformers pointed at the latest set of point"s, which are combined according to the value of the a posteriori probability for each pointing direction.

在该算法中,期望信号的波达方向被看作是一个定义在若干候选波达方向上的离散随机变量,由阵列接收信号计算出各候选波达方向的后验概率,并将后验概率的分布作为是否需要进行二次采样的判断标准;随后,对各波达方向上的波束成形权值线性加权,便可得到自适应波束成形器,权系数为各候选波达方向的后验概率值。

By means of proposing a priori Markovian transition probability used in the model predictive probability in input synthesize, the IMM estimation algorithm not only utilizes the sufficiency system's posteriori information, but also utilizes rationally the system's priori information, which enhances estimation performance highly Theoretical analysis and simulation show the IMM algorithm is one of the most cost-effective schemes in all generalized pseudo Bayesian algorithms.

IMM估计方法通过在用于输入综合的模型预测概率中引入一个马尔可夫先验转移概率,使得IMM估计不但充分地利用了系统的后验信息,而且合理地利用了系统的先验信息,从而大大地提高了估计的精度和性能。理论分析和仿真结果表明:IMM估计方法是各种广义伪贝叶斯算法中性能最优的一种自适应估计算法。

This paper presents a novel multiple object segmentation algorithm based on a Bayesian framework. According to the characteristic of the intra-frame and inter-frame information, a representation of Maximization of the A posteriori Probability of spatio-temporal label field is proposed. So a minimization of energy function is obtained.

摘要该文提出了一种基于贝叶斯框架的时空标记场最大后验概率的多视频对象分割算法,根据视频序列帧间和帧内信息的不同特点,建立基于多个对象分割标记场的最大后验概率公式,并导出其最小能量函数,通过求解最小能量使其分割标记的后验概率达到最大。

Meanwhile, for the characteristics of plant disease spot, segmentation model was created by utilizing the local correlated characteristic of Markov random field and linear stationary auto-regression model formed by Gauss distribution, and self-adaptive segmentation of plant disease spot was realized through optimizing the model with improved ant colony algorithm and maximum a posteriori probability estimation of Gauss-Markov random field.

同时,利用Markov随机场的局部相关特性并结合Causs分布组成线性平稳自回归模型,针对植物病斑特征建立分割模型。最后,采用改进型蚁群算法对其进行优化,并结合Gauss-Markov随机场最大后验概率估计,实现对植物病斑的自适应分割。

ALSAB adopts Maximum A Posteriori provability estimation and Expectation-Maximization algorithm to estimate the weight parameters of LSA,and ALSAB employs incremental learning to decrease accumulative effect caused in continuous update with considering that the probability of uncommon words decreases in continuous update.

ALSAB采用最大后验概率估计与期望值最大算法对概率LSA模型参数进行有效的估计,在充分考虑多次更新中不常用字词概率参数降低问题的前提下,采用增量学习方法降低多次更新产生的累积效应。

The Bayesian estimation is derived through statistical analysis and it is shown to be equivalent to the maximization of the a Posteriori Probability.

通过理论分析得到了简化的贝叶斯信道估计权值,其等同将后向概率的最大化。

This paper proposes an iterative Maximum A Posteriori probability channel estimation algorithm for MIMO-OFDM systems.

摘要该文提出了一种适用于MIMO-OFDM系统的迭代最大后验概率(Iterative-MAP)信道估计算法。

This paper presents an improved maximum a posteriori probability decoding algorithm for optimal decoding of parallel concatenated convolutional codes.

摘要该文给出了一种改进型最大后验概率译码算法用于实现并行级联卷积码的最优译码。

First, the optimal maximum a posteriori probability Turbo JD is analyzed, to which a simple scheme is then proposed.

文章首先讨论了最优最大后验概率Turbo JD算法原理,并对该算法提出了一种简化处理方案。

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在对危险的南部地区访问时,他斥责什叶派民兵领导人对中央集权的挑衅行为。

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