1) independent component analysis
独立成分分解
1.
Based independent component analysis,estimation method for multivariate conditional higher mom.
提出了多元GARCHSK模型并给出其向量表达,用独立成分分解技术来解决多元GARCHSK建模中的“维数灾难”问题,给出多元条件高阶矩波动率的估计方法。
2) independent component
独立成分
1.
Chinese independent component and English parenthesis have some in common in basic features,but there are great differences in specific ways of expression,expressing customs,the internal composition and location forms.
汉语的独立成分与英语的Parenthesis(插入语)在基本的性质特点上有相同之处,但在具体的表现方式、表达习惯、内部构成及位置形式上却存在较大的差异,本文试从中西文化背景和中西思维方式两个方面分析汉英两种语言中独立成分差异产生的原因。
2.
The traditional independent component analysis(ICA)algorithms were based on contrast functions defined in terms of a single fixed nonlinear function as the measurements of independence.
传统独立成分分析用一个固定的非线性函数作为独立性度量和对照函数,而对独立成分服从不同非高斯分布的情况没有细分。
3.
To overcome the problems mentioned previously, which is the key hindrance in content-based image retrieval; we proposed a new retrieval method, which is trying to find some independent components from the image database.
独立成分分析(Independent Component Analysis,简称ICA)是近期发展起来的一种非常有效的盲信号处理技术,该方法在基于内容的图像检索领域也发挥着越来越重要的作用。
3) independent component analysis (ICA)
独立成分分析
1.
A local regression method was proposed based on independent component analysis (ICA) .
建立了一种基于独立成分分析的局部建模新方法,该方法首先将独立成分分析(ICA)用于近红外光谱的特征提取,然后,根据所提取的独立成分选择校正集中与预测样本相邻近的样本构成校正子集,建立局部偏最小二乘(PLS)回归模型并对预测样本进行预测。
2.
To overcome the shortcoming of the conventional process monitoring methods assumption that the extracted features must be subject to multivariate normal distribution, a novel method based on independent component analysis (ICA) and principal component analysis (PCA) was presented for process performance monitoring by using a two-step procedure.
为克服传统过程监控方法需假设过程特征信号服从多元正态分布的缺陷,提出了一种新的基于独立成分分析(ICA)和主元分析(PCA)的过程监控方法,该方法由两步组成:第一步:利用独立成分分析方法从过程信息中提取非正态分布特征信号,然后用Parzen窗法估计其概率密度确定控制限进行过程监控;第二步:利用主元分析方法对剩余过程信息提取正态分布特征信号,采用Q和HotellingT2统计量对此正态特征信号进行过程监控。
3.
In this paper, we show the basic mathematic model and separated algorithms of blind source separation (BSS)/ independent component analysis (ICA) firstly, we discuss in more detail uniqueness issues about the nonlinear BSS/ICA problems.
本文主要阐述了非线性盲源分离(BSS)/独立成分分析(ICA)模型的基本数学原理、分离算法、算法性能及其应用。
4) independent component analysis(ICA)
独立成分分析
1.
A new model building method of near-infrared(NIR) spectra based on independent component analysis(ICA) and support vector regression(SVR) was proposed.
首先采用独立成分分析(ICA)提取近红外光谱数据矩阵的独立成分和相应的混合矩阵,然后用支持向量机回归(SVR)对混合矩阵和实测浓度矩阵进行建模,建立了独立成分分析-支持向量机回归(ICA SVR)的近红外分析建模方法。
2.
Independent component analysis(ICA) is a new method of signal statistical processing and widely used in many fields.
独立成分分析是一种新的信号处理统计方法,被广泛用于各个领域。
3.
This paper proposes a dimensionality reduction and compression method of hyperspectral images based on Independent Component Analysis(ICA) for hyperspectral image analysis.
该文提出了一种以高光谱图像分析为目标的基于独立成分分析的高光谱图像降维和压缩方法。
5) independent component analysis (ICA)
独立成分分析(ICA)
6) independent component analysis(ICA)
独立成分分析(ICA)
补充资料：独立可测分解
独立可测分解
independent measurable decompositions
独立可测分解【诚脚即白皿n粉s切门ble奴.即因d临;ne3绷e邢Moe，3Me四M砒pa36oe。。」，独立可测分划(汤配讲血北nt nl改昭urable partj石ons)，正规化测度空向的 两个可测分解亡与叮，满足条件:若B(幻与B(衬分别为完全由亡与叮的元素组成的可测集的BOole口代数，则其中之一的元素依概率论意义与另一个的元素独立.即对姓6刀(亡)，B任B(粉)有料(A自B)三一爪A知(B).在这些条件下，如果一个可测分解作为古与叮两者的改进，依nldo合于单点分解，则亡与叮称为独立补(汤由详n山泊tcomP坛m改lts).在h加卿犯空间(玩b留gllesPace)中可测分解具有独立补的条件是已知的.【补注】亦见可测分解(In已班切旧bk decomp招ition).
说明：补充资料仅用于学习参考，请勿用于其它任何用途。
参考词条