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- Parzen probability density estimation Parzen窗口概率密度估计
- kernel probability density estimation 核概率密度估计
- The binned kernel density estimators were exploited to estimate the probability density function of background intensity in training sequence. 该模型采用分箱核密度估计算法从训练图像序列中得到背景的密度函数。
- Partially Supervised classification of remote sensing images through SVM-based probability density estimation 穿过基于SVM概率密度估计遥感成象的部分控制分类
- Digital modulation classification using probability density estimation and support vector machine 利用概率估计和支持矢量机的信号调制分类
- Keywords ethology;posture;naive Bayes classifier;invariants;probability density estimation; 关键词行为学;体态;朴素贝叶斯分类器;不变量;概率密度估计;
- probability density estimation 概率密度估计
- For the accident assessment probability density function can be used to solve the uncertainties of estimation of the source intensities. 应用几率密度函数可解决事故预测时源强估算的不确定性问题。
- Since it is the probability density, it must be single-valued. 因为它是几率密度,因此必须是单值的。
- Methods Non-parameter kernel density estimation method was adopted. 方法采用非参数核密度估计推断方法。
- We get a buildup of electronic probability density between the nuclei. 我们得到在两个核间的电子几率密度的堆积。
- In this paper,a new crowd density estimation technique is proposed. 论文提出了一种新的人群密度自动估计方法。
- Sample Percentage Presentation of Joint Probability Density of Two Random Variables. 二维随机变数联合机率密度之取样百分比。
- The analytic solutions of the probability density of the steady-state responses of Coulomb sliding systems with gradually strong springs to Gaussian white noise are derived. 利用等效线性化方法推导了具有渐硬非线性复位弹簧的滑动系统的高斯白噪声激励稳态随机响应概率分布的解析解。
- probability density function estimation 概率密度估计
- If cumulative is TRUE, EXPONDIST returns the cumulative distribution function; if FALSE, it returns the probability density function. 如果cumulative为TRUE,函数EXPONDIST返回累积分布函数;如果cumulative为FALSE,返回概率密度函数。
- In this paper, the method of generating random number with given probability density function is proposed by using vertical density representation. 摘要本文首先介绍基于垂直概率密度表示的,给定密度函数的随机数生成的通用方法;
- The structure of PMN is a four layer feedforward neural networks(FNN), where the Gaussian probability density function is realized as an internal node. PMN网为一个四层前馈网,它构成一个贝叶斯分类器,实现多类分类的贝叶斯判别,把输入的说话人语音数据模型参数通过网络变换为输出的说话人判定。
- Based on the diffusion equation, the transition probability density of stock prices is calculated by means of the Monte-Carlo method. 摘要在扩散方程对股价运行描述的基础上,用蒙特卡罗方法得出未来某一时刻股价转移概率密度的数值解。