Chinese translation for "intrinsic dimensions"

固有维数

Related Translations:

intrinsic necessity:  内在必然性

intrinsic strength:  本征强度内在强度

intrinsic contaminant:  固有杂质

intrinsic transistor:  本征晶体管

intrinsic brightness:  本征亮度固有亮度内禀亮度

intrinsic numeric:  本质数值

intrinsic ash:  内在煤灰

intrinsic layer:  本征层

intrinsic incubation:  内潜伏期

intrinsic admittance:  固有导纳

Example Sentences:

	1.	In section 4 . 2 we analyze its main idea and algorithm in detail , two relevant theorems included ; section 4 . 3 provides plenty instances so to explain its nonlinear dimension reduction ability , section 4 . 4 propose a combined method that integrates the advantage of various methods . in section 4 . 5 we analyze some significant problems in lle , including the locality of manifold representation , the choice of the neighborhood , the intrinsic dimension estimation and the parametric representation of mapping . in section 4 . 6 we design an algorithm for estimating the intrinsic dimension in the base of locally linear approximation and discuss the choice of its parameters 第四章是本文的重点内容，研究一种全新的非线性降维方法? ?局部线性嵌入方法，对它的思想和算法进行了详细的分析，给出算法两个相关定理的证明；第三节对比主成分分析，通过实例说明局部线性嵌入方法的非线性降维特征；第四节在此基础上提出了旨在结合两者优势的组合降维方法；第五节提出了局部线性嵌入方法中存在的若干关键性问题，包括流形的局部性、邻点的选择、本征维数的估计和降维映射的表示，第六节基于局部线性近似的思想提出了一种本征维数的估计方法，设计了实用算法，结合实例对算法中参数的选取进行了讨论；最后一节提出了一种基于局部线性重构的图形分类和识别方法，将其应用于手写体数字的图像分类识别实验，实验得到的分类准确率达96 . 67 。
	2.	In the first and second section of chapter 1 we introduce the model of dimension reduction problem , put forward the concepts of dimension - reduction function and embedding function , and make a classification for the dimension reduction problem ; in section 1 . 3 we discuss " the curse of dimension " and the sparsity of high - dimensional space ; in section 1 . 4 we discuss " intrinsic dimension " and its estimation based on the model of dimension reduction 第一章首先提出了降维的模型和定义，讨论了相关的问题；第三节讨论“维数祸根”现象和高维空间的稀疏性，通过实例分析其对高维空间的数据分布特性具体影响；第四节讨论了本征维数及其估计的基本问题。
	3.	In last section we propose a new method for image classification and recognition , and the result of experiment shows that the method is effective with classification accuracy of 96 . 67 % . the main creative points in this paper are : propose the concepts of dimension - reduction function and embedding function , define the projection index in term of linear operator and prove two relevant theorems ; design a method to estimate the intrinsic dimension ; put forward an classification algorithm based on lle 本文的主要创新点在于：提出了降维映射和嵌入映射的概念；给出了投影指标的严格定义，证明了两个相关定理；提出了一种用于估计本征维数的方法并设计了实用算法；提出了一种基于局部线性重构思想的分类和识别方法。

Similar Words：

"intrinsic detector" Chinese translation, "intrinsic detrusor pressure" Chinese translation, "intrinsic differential geometry" Chinese translation, "intrinsic differentiation" Chinese translation, "intrinsic diffusion coefficient" Chinese translation, "intrinsic dispersion" Chinese translation, "intrinsic displacement" Chinese translation, "intrinsic dissolution rate" Chinese translation, "intrinsic dissymmetry" Chinese translation, "intrinsic dynamic viscosity" Chinese translation