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A new symbol-constrained joint source-channel decoding algorithm for VLCs is presented.By constructing double-tree VLCs sources,the propagation-error problem is evidently alleviated.Meanwhile,by applying symbol-constrained method to MAP algorithm,not only the a priori probability of VLCs sources is efficiently utilized,but also the Symbol Error Rate is reduced enormously.

提出了一种新的针对不等长编码信源的符号约束MAP联合译码算法,利用VLCs双树信源的构造方法,有效地抑制了VLCs的错误扩散;同时,通过将"符号约束"的思想应用于最大后验概率译码算法,不仅充分利用了信源先验信息,而且极大地降低了误符号率。

Alternating minimization cost function and maximization poster probability is proposed to restore the blurred image. The method is divided two step, one step is EM step, it is to estimate the PSF by using minimimum-error criteria, the other step is M step, we use MAP criteria to restore the blurred image.

EMM方法分为两个步骤,第一个步骤是EM步骤,利用最小恢复残差准则,估计系统的点扩散函数PSF,第二个步骤是M步骤,利用最大后验概率准则恢复模糊图像。

This paper based on Bayes posterior probability formula, establishes a dynamic model for the identification of fractures by using five performance paramete1 such as water breakthrough period, waterline movement velocity, using velocity of water cut, cumulative injection production ratio, and injection pressure. It carries out an analogy between the samples to be distinguished and the known ones to confirm how to classify them.

将油水井见水周期、水线推进速度、含水上升速度、累积注采比、注水压力等5个参数作为动态变量,基于Bayse后验概率公式建立动态裂缝识别模型,将待判别的样品与已知类型的样品进行类比,以确定待判别样品的归类。

The situation after the first M step is shown in plot, in which the mean of the blue Gaussian has moved to the mean of the data set, weighted by the probabilities of each data point belonging to the blue cluster, in other words it has moved to the centre of mass of the blue ink. Similarly, the covariance of the blue Gaussian is set equal to the covariance of the blue ink.

图显示了初始的 E 步骤,用红色表示用红色 component 产生的后验概率,蓝色也是同样的情况,还有一些不太确定的点是用紫色显示的,在图中蓝色的高斯的均值已经移到了蓝色数据集的中心上,类似的,蓝色高斯的协方差设为蓝色点的协方差。

A novel MAP image restoration method in Dual-tree Complex Wavelet Transform domain is proposed.

提出了一种双树复小波变换域最大后验概率图像复原方法。

In the new algorithm, SCA provides global convergence by moving the equalizer weight vector in the correct direction. After the equalizer enters the local convergence region, SDD can decrease the residual inter-symbol interference and accelerate convergence speed by maximizing the posteriori probability of the equalizer output.

该算法一方面使用了SCA算法来提供全局收敛,保证在整个收敛过程中,均衡器朝正确的方向收敛;另一方面当均衡器进入到局部收敛区域时,并行增加的SDD部分通过最大化均衡器输出的局部后验概率来降低剩余码间干扰和提高收敛速度。

In the basis of Bayes principle, the linearized Zoeppritz equation and convolution model are applied to obtain the posterior probability density of the lithology model.

在贝叶斯原理的基础上,通过Zoeppritz方程简化公式及褶积模型建立反演参数的后验概率模型。

It employs a shrink training algorithm base on the deterministic annealing global optimization technique. This training algorithm adopts a maximum a posteriori optimization criterion.

它采用了一种基于确定性退火全局优化技术的收缩训练算法,这种算法以最大后验概率为优化标准。

The stability of the established discriminant function and the reliability of the results of the evaluation were enhanced.

对实例评价结果表明:通过筛选引入判别方程变量的后验概率均达到90%以上,对判别分类有显著影响,从而提高了所建立的判别函数的稳定性和评价结果的可靠性。

The uncertainties of the parameter estimation are analysed in terms of the posterior probability distributions of inversion results.

最后利用参数的后验概率分析反演结果的不确定性。

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