Gaussian classifier
英
美 [ˈgaʊsiən ˈklæsɪfaɪər]
【计】高斯分频符
双语例句
- Reinforcement Learning for Continuous Spaces Based on Gaussian Process Classifier
基于高斯过程分类器的连续空间强化学习 - Because cyclic higher-order statistics can depress Gaussian noise, cyclic higher-order cumulant can be used to structure invariants of classifier.
由于高阶循环统计量具有抗平稳噪声的能力，从而在高阶循环累积量域构成了分类特征不变量。 - Proposed is a hybrid neural network classifier with high performance and simple structure that makes a substitution for the highly complex Gaussian mixture model ( GMM). This classifier is composed of a self-organizing map neural network ( SOFMNN) and a probabilistic neural network ( PNN).
针对这样的问题，提出一种高性能、结构简单的基于自组织映射（SOFMNN）和概率神经网络（PNN）的混合神经网络分类器以取代目前常用的高斯混合模型（GMM）分类器。 - It is proven that the solution of one-class SVM using the Gaussian kernel can be normalized as an estimate of probability density, and can be used to obtain the Bayesian classifier.
证明采用高斯核的一类SVM，其解可以归一化为密度函数，并把该密度函数看作类条件概率密度的平滑估计，构造贝叶斯分类器。 - This paper principally discusses the training problem of Gaussian basis function classifier which can be used for classification. For basis function classifier, how to correctly initialize the number of network hidden nodes and their parameters is very important.
本文主要研究高斯基函数分类器的训练问题，对基函数分类器来说，如何确定网络的初始隐层节点数和隐层节点参数是一个重要问题。 - The Comparison between SVM with Gaussian Kernel and Radial Basis Function Classifier
具有高斯核函数的支撑矢量机与径向基函数分类器的比较 - In this approach the eigenvectors of power signals to be discriminated, which are analyzed and processed by adaptive Gaussian representation ( AGR), are input into neural network classifier.
将经过自适应高斯基表示（AdaptiveGaussianRepresentation，AGR）分析处理的电力信号特征向量输入神经网络分类器进行识别。 - The pixel level frame/ field difference statistic is used by film mode detection based on gaussian classifier.
该技术利用逐像素的帧、场变化统计以及基于高斯分类的电影模式状态识别对电影模式源进行检测和处理。 - In the model training and recognition module, author use the Gaussian mixture model as a classifier, which in comparison with other classifiers, can better identify abnormal audio difference.
在模型训练与识别模块中，使用了高斯混合模型作为分类器，它与其他分类器相比，能更好的分辨出异常声音的差别。 - We adopt the output of Gabor filters as feature and Gaussian mixture model ( GMM) as the classifier.
本文采用Gabor滤波器的输出结果作为特征，高斯混合模型（GMM）作为分类器对织物瑕疵分类。 - Then the study utilizes the Linear Discriminant Classifier, Quadratic Discriminant Classifier, Support Vector Machine, SVM ( containing Gaussian kernel) as well as the k-Nearest Neighbor Classifier in the experiment.
再分别利用线性判别分类器、二次判别分类器、支持向量机（含高斯内核）以及k值-最近的邻位序列分析分类器进行实验。