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hypersphere相关的网络例句

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与 hypersphere 相关的网络例句 [注:此内容来源于网络,仅供参考]

The fuzzy membership value to each input point is computed according to the distances to the center of hypersphere.

该方法提高了最小二乘支持向量机的抗噪声能力,尤其适用于未能完全揭示输入样本特性的情况。

In this paper, it is extended to image 3D modeling which tries to find the smallest hypersphere enclosing target data in high dimensional space by kernel function.

本文通过在高维空间中寻找包围目标数据的最紧的超球,将球型支持向量机扩展到图像3D建模的应用中。

How many equal three-dimensional spaces would a hypersphere be cut into by hyperplanes at right angles to each other?

一个超球面被切割成相互垂直的超平面会产生多少三维空间?

Each clustered pattern set is a fuzzy set hypersphere with a corresponding membership function. A pattern class is the combination of the pattern sets.

模式集是一个具有超球核的用隶属函数表示的模糊集,模式集又可以合并成模式类。

Thus, we propose a new depth function to deal with such concave shape data sets using the principal of smallest hypersphere in the Gaussian kernel feature space.

本文从样本深度的角度,利用高斯核特征空间最小球原理,提出了一种广义的数据深度。

The fuzzy hypersphere support vector machine is proposed for shallow buried target discrimination, and its two aspects, hyperparameter optimization and kernel function selection, are comprehensively studied.

提出了模糊超球面支持向量机浅埋目标鉴别算法,并对FHS-SVM的超参数优化和核函数选择两个问题进行了深入研究。

If the mansion stood on a hypersphere slightly greater in diameter than the mansion grounds, a person could move from any point to any other with what, in three-space, would seem to be right angles.

如果这座大厦建造在一个比地基更多维的超球面上,一个人就可以从任意在三维空间内看上去是直角的地方从一点移动到另一点。

In this algorithm,the fuzzy hypersphere membership functions of the state estimation of local filters are combined with the weights of the fusion network,and the weights of the network can be adjusted online,so that the whole estimation is adaptive and fault-tolerant.

该算法将局部滤波器状态估计的模糊超球隶属函数引入网络,在线调整融合网络权值,实现全局估计的自适应性和容错性。

Using the fuzzy membership model based on support vector data description, the membership values to each input sample is computed according to its distance to the center of the hypersphere with minimal volume containing all objects.

利用一种基于支持向量数据域描述的模糊隶属度函数模型,根据样本到特征空间最小包含超球球心的距离来确定模糊隶属度。

A fuzzy membership model based on support vector data description is proposed to fuzzify all the training data. Then the model is introduced into least square support vector machines. Data samples in input space are mapped into a high dimensional feature space, and then the smallest enclosing hypersphere is found.

将模糊隶属度概念引入最小二乘支持向量机,提出一种基于支持向量数据域描述的模糊隶属度函数模型,将输入空间中的样本映射到一个高维的特征空间;然后根据其偏离数据域的程度赋予不同的隶属度。

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