先验概率

基于GIS改进先验概率的遥感土地利用/土地覆盖分类研究

Remote Sensing Land Use / Land Cover Classification by Using GIS to Improve the Prior Probability

其次基于最小错误率原理选取SAR图象自动分割阈值，在先验概率未知和估计条件下，获得目标及其阴影区域的检测结果；

Second , on the basis of the principle of minimum error ratio , thresholds are computed in both a prior probability is unknown and known respectively .

该算法需要在训练阶段采集无线连接TCP本地延迟抖动训练样本集以获取无线连接上的TCP本地延迟抖动先验概率分布。

This algorithm get wireless TCP Local Delay Jitter prior probability distribution from wireless connnections ' TCP Local Delay Jitter training set in the training phase .

半平面MRF（MarkovRandomField）模型描述线过程的分布，以确定各个子模型的先验概率。

In order to determine the a priori distribution of these submodels , a half plane Markov random field model is utilized to describe the distribution of the line process .

先验概率可以根据马尔可夫随机场（MRF）和吉布斯分布（GD）的等效性，用GD的概率估计。

The prior probability can be estimated by using the equivalence of the Markov random fields and the Gibbs Distribution ( GD ) .

应用Bayes判别原理，引入误判成本和先验概率，构建了一个简明的违约判别模型，经检验模型是统计有效的，判别结果也是较好的。

We construct a simple default judgment model applying Bayes judgment principle , misjudgment cost and priori probability . The model is tested effective with good results .

采用Bayes方法修订马尔可夫过程的状态转移概率矩阵；将先验概率分布修订为后验概率分布；

By means of Bayes formula , state transition probablity matrix of Markov process was revised , and prior probablity distribution was modified into posterior probablity distribution .

以CART方法建立胃癌最佳判别模型，诊断进展期胃癌先验概率的敏感度为91.9%，特异度为90.7%；

The diagnostic model for gastric cancer was formed by CART . The models ' sensitivity and specificity of priori probability were 91.9 % and 90.7 % respectively .

为计算每个专家的权重，采用高斯混合（Gaussianmixturemodel，GMM）模型对低维流形空间中的数据分布进行概率建模，得到各个专家的先验概率和先验分布形式。

In order to calculate the gating of each expert , Gaussian mixture model ( GMM ) is used to approximate the probability distribution over the manifold space to obtain the prior probabilities and distribution models of experts .

在目标识别级重点讨论了基于D-S证据理论的目标识别融合，通过性能分析可知该算法具有不需要先验概率和条件概率密度等优点。

In object identification level object identification fusion based on D-S proof theory was discussed , performance analyzing is found that the arithmetic did not need probability distribution .

本文尝试利用GIS软件对地理数据进行分析和预处理，对考虑先验概率是否提高Bayes监督分类精度这一问题作了探讨。

Supported by the analysis and advance process to the geographical data using GIS software , the paper discusses the question that whether the accuracy of Bayes supervised classification will be improved considering the influence of the prior probability .

对69个中国儿童（7~16岁）的脑结构磁共振图像，用改进的优化方法建立了中国儿童T1脑模板和先验概率图。

The Chinese pediatric T1 brain template and apriori maps are constructed using improved optimized protocol from sixty-nine Chinese children ( 7 ~ 16 years old ) magnetic resonance imaging ( MRI ) data .

本方法原理上推广了Viterbi译码算法，形成一个需要兼顾信道编码序列流的最优路径与多路信源编码状态转移树中的最大先验概率的译码算法。

Our method generalize the conventional Viterbi decoding algorithm , not only the optimal path in channel decoding trellis but also the a priori probability of branches in multiple VLC source trees are considered .

由辅助数据中计算各类别面积比率作为先验概率，替换传统监督分类中的先验值，并进一步对先验概率进行迭代，最后利用改进的先验概率对LANDSATTM影像进行分类实验。

The proportion based on the assistant data is used as the prior probability to replace the prior value in the conventional supervised classification ; the farther iterative prior probability is applied into classifying progress on Landsat TM image .

该算法在初始迭代采用MAP算法估计接收信号的先验概率分布以获得较精确的先验概率分布，迭代时采用SIC算法以方便计算和实现，仿真说明该算法有效地提升了系统的均衡效果。

In the initial iteration of the algorithm , using MAP algorithm to estimate the prior probability distribution of the received signal , it is more accurate than using the SIC algorithm . The SIC algorithm was used in the iterative process , to facilitate the calculation and implementation .

概率神经网络分类器在各类别先验概率相等的条件下等价于基于核函数的bayes分类器，可以实现在分类误差最小意义上的最优分类。

Probabilistic neural network classifier , under certain condition that the a priori probabilities of all classes are equal , is equivalent to the Bayes classifier based on the kernel function , and can achieve minimum error in classification on optimal classifier .

在监督分类中，对训练区（AOI区域）的选择、钝化及先验概率的确定作了描述，并介绍了本文中采用的建立在贝叶斯（Bayes）准则基础上的最大似然分类法的原理。

In the supervised classification , the election and passivation of the AOI and confirmation of the prior probability are described , and the principle of the maximum likelihood classification based on Bayes rule in the paper is introduced .

近几年来采用的基于雷达接收机工作特性曲线即ROC曲线的评估方法得到的评估结论不敏感于类别先验概率，从根本上克服了以上指标的缺陷。

Recently the ROC curve evaluation method is widely used and developed , because the evaluation conclusions based on the ROC curve is insensitive to the prior probability of classes and it overcomes the defects of the previous commonly used evaluation measures .

考虑到传统最大似然分类（MLC）方法包括先验概率和条件概率密度函数两个核心环节，提出基于空间信息的浮动先验概率MLC方法，融合空间信息和波谱信息，以提高分类精度。

Considering two stages probability method of maximum likelihood classification ( MLC ), this article proposed a new method of exploiting spatial information to improve classification rules by adjusting the prior probability according to the local spatial information .

该算法利用马尔可夫随机场（MRF）作为彩色图像恢复的先验概率分布模型，在模型中采用8邻域的线过程来表征和提取多色彩通道间的相关性。

It specified a Markov random field ( MRF ) model for the prior probability distribution of the degraded color image . The line process for an 8-point neighborhood system was developed to characterize and extract the spatial interaction among different color bands .

该方法采用期望最大化（EM）算法来估计联合分布参数，基于语音和噪声的先验概率密度，在倒谱域中对语音特征参数进行最小均方误差预测（MMSE），以提高语音识别精度。

The method evaluates the parameters of the joint distribution using the expectation maximization ( EM ) algorithm . The minimum mean squared error ( MMSE ) estimator for the speech feature parameters in spectrum-domain based the prior probability distribution is to enhance the correctness of speech recognition .

本文对估计DDR中先验概率的两种方法（SAMK和SAMD）进行了较为详细的比较讨论。

In this paper , two methods ( SAMK and SAMD ) of estimating the prior probability in DDR ( Decission-Directed Receiver ) are discussed and compared in detail .

在最近二十年里，一些国内外相关文献指出FMM没有考虑将邻域像素间的空间关系引入到先验概率分布中导致分割结果对噪声的干扰非常敏感。

In the recent decade , some related literature at home and abroad pointed out that , because the finite mixture model doe not incorporate the spatial relationship between neighboring pixels into the prior , the image segmentation results are sensitive to noise .

同时，根据Pollard（1993）的分析，显著性水平提供的是I型错误的条件先验概率和I型错误的整体先验概率的上限，而不是I型错误的条件后验概率。

05 should be considered with caution or tolerance . Meanwhile , according to Pollard ( 1993 ), what significant level provides is the conditional prior probability and the upper bound of the whole prior probability , rather than the conditional posterior probability of a Type I error .

先验概率和似然函数未知时的分布式检测融合

Optimal distributed detection fusion with unknown priori probabilities and likelihood functions

基于先验概率模型的自适应背景图像分割算法

New adaptive algorithm for segmenting image background based on prior probability model

基于模糊先验概率的期望效用模型

Expected utility model based on fuzzy prior probability

在融合过程中以贝叶斯概率模型修正先验概率。

The prior probability is amended by Bayesian probability model in the fusion process .

基于地物空间信息的浮动先验概率最大似然分类研究

Study on Floating Prior Probability MLC Based on Spatial Features and Local Spatial Autocorrelation

这些方法均在不同程度上要求专家给出一些先验概率值，从而影响了它们的应用程度。

Because the methods are all based on prior probability , their applicability is constrained .