Hypersphere

Ultra-Wideband Synthetic Aperture Radar Unexploded Ordnance Detection Using HMM Kernel Hypersphere Support Vector Machine

基于HMM核超球面支持向量机的超宽带SAR未爆物检测

Characteristics of the hypersphere in Euclidean space

欧氏空间超球面的特征

Engine fault diagnosis based on probability hypersphere set neural network

基于概率超球集神经网络的发动机故障诊断

A Integrated Navigation Fusion Algorithm Assisted by Fuzzy Hypersphere Neural Network

模糊超球神经网络辅助组合导航融合算法

A structure optimization of the radial basis probabilistic neural network based on covering hypersphere algorithm

一种基于覆盖超球算法的径向基概率神经网络结构优化

Neural Networks of Fuzzy Hypersphere Barycenter Clustering

模糊超球质心聚类神经网络

The class-aggregating algorithm of the fuzzy hypersphere neural networks use a form factor θ to realize a supervised learning .

模糊超球神经网络的聚类学习算法采用形状因子θ实行有指导的学习。

Characterization of the Hypersphere in Euclidean Space

关于欧氏空间中超球面的特征

The Regular Simplex Incribed In A Hypersphere Has Maximal Volume

超球的内接单形的最大体积&献给柯召老师八十诞辰

A construction theorem about a polytope circumscribing a hypersphere

超球内接凸多胞形的一个构造定理

Based on the fundamental rules of human brain 's analyzing and reasoning in clustering , this paper proposes a learning algorithm of neural networks of fuzzy hypersphere barycenter Clustering .

基于人的大脑进行聚类分析所遵循的基本原则，提出了一种模糊超球质心聚类神经网络学习算法。

Fuzzy hypersphere support vector machine ( FHS-SVM ) has stronger generalization capability than hyperplane support vector machine in the one-class classification problem , being successful in radar target detection .

模糊超球面支持向量机（FHS-SVM）在处理一类分类问题时比超平面支持向量机泛化能力更强，特别是在雷达目标检测中得到了成功应用。

Circumscribed Hypersphere and Escribed Hypersphere of a Tetrahedron in Lobachevsky 's Space

罗氏空间中四面体的外接球曲面及旁切球曲面

As one class classifier , which is a variant of support vector machine , can establish the normal data hypersphere realize fault detection and the establishment of various fault hypersphere to realize fault diagnosis .

作为单类分类器，SVDD方法是支持向量机（supportVectorMachine，SVM）的变种，可以建立正常数据超球面实现故障检测和建立各类故障超球面实现故障诊断。

In this paper , we establish the Cauchy integral formula and Schwarz integral formula , and discuss the sufficiently and necessary condition of B-harmonic function on the hypersphere topological product domains .

建立了超球拓扑积上的Cauchy积分公式和Schwarz积分公式，并进一步讨论了超球拓扑积上B-调和函数的充要条件。

Through adopting the ideas of optimal hypersphere and constructing a quadratic programming problem , we can construct a similarity measurement matrix by support vectors taking place of samples , which can solve uncertain problem dimensionality .

该方法借鉴了最优超球面思想，通过构造一个二次规划问题，运用支持向量代替样本构造相似度度量矩阵，从而解决了不确定问题维度对计算复杂性的影响。

When a training sample set is unlabelled and unbalanced , attack detection is treated as outlier detection or density estimation of samples and one-class SVM of hypersphere can be utilized to solve it .

针对训练样本是未标定的不均衡数据集的情况，把攻击检测问题视为一个孤立点发现或样本密度估计问题，采用了超球面上的One-ClassSVM算法来处理这类问题；

As for the problem that training samples in anomaly detection are unlabelled and unbalanced data sets , attack detection is treated as outlier detection and one-class SVM of hypersphere can be utilized to solve it .

针对异常入侵检测中训练样本是未标定的不均衡数据集的情况，将其视为一个孤立点发现问题。提出了适用于孤立点检测的超球面One-ClassSVM的异常检测算法。

The problem of hypersphere range search in high dimensional space is : give a set of points in high dimensional space , input a point and a radius value , inquire about the number of points in given set these points are included in the hypersphere .

在高维空间中点的超球范围查找问题是：已知一个高维数据点集，输入一个点和半径数值，询问所确定超球范围内包含有给出点集中哪些点。

In order to improve the accuracy of clustering separation , this paper selects all data-points outside the hypersphere of a given radius centered at origin , in mixture space , and then projects the data points onto the unit hypersphere centered at origin to obtain the aggregate Cy.

为了改善聚类分离的精度，该方法选取混合空间中半径给定的、中心位于原点的超球面以外的所有数据点，然后将这些数据点映射到中心位于原点的单位超球面上以得到集合Cy。