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    2) A physical explanation for both the aliasing and the "Independent Source" of EEG were given.
    Principle component analysis extracts the image gray characteristics considering the second order moments, while independent component analysis accounts for higher order statistics and identifies the independent source component from their linear mixtures.
    它去除了各特征分量之间彼此的相关性,并且可以根据其对应的特征值的大小确定它在整个能量中占据的百分比,从而可以分离出信号中的主要成分和次要成分; 独立成分分析从图像的高阶统计特性出发,提取图像的灰度特征。
    For maximum nongaussianity estimation, uniqueness means that there is a one-to-one correspondence between local maxima of nongaussianity and independent sources.
    Independent component analysis (ICA) is a newly developed and powerful technique for recovering latent independent sources given only their mixtures.
    独立分量分析(Independent Compondent Analysis:ICA)是近年来提出的非常有效的数据分析工具,它主要用来从混合数据中提取出原始的独立信号。
    Therefrom, this thesis puts forward the shock model with seven individually independent sources and structure three-dimensional exponential distribution, which its edge distribution is only bivariate distribution of Marshall-Olkin.
    When some certain assumptions are satisfied, ICA can effectively separate the independent source signals from the synchronous multichannel recording, and then according to some independent sources, we can further analyze their physiological significance.
    It was initially thought that the lung was resistant to ischemic injury because of its dual pulmonary and bronchial arterial blood supply and its independent source of oxygen, available from the alveolar space.
    As ERP is contaminated with EEG, Various recorded biomedical signals practically are mixture of different independent source signals , artifacts and noises, such as EOG、ECG、EMG and other noises.
    The aim of ICA is to recover independent source signals from mixed signals when sources and mixed parameters are unknown which make ICA has high practical value and wide application.
    它是一种自适应优化算法,着眼于数据间的高阶统计特性,其本质是在源信号和混合参数均未知的前提下,能仅根据源信号的一些基本统计特征(统计独立和非高斯分布),由混合信号恢复出源信号。 这一特点使得独立分量分析技术具有很高的实用价值和广阔的应用前景。
    Independent Component Analysis (for short ICA) is a new signal analysis method, which is derived from the developing Blind Sources Separation technology of multi-channel recently. ICA is a signal processing method on the condition that there only are observing signal data and unknown mixed method of the signals extracts independent source signals.
    独立分量分析(Independent Component Analysis,简称ICA)是一种较新的信号分析方法,它是近年来由盲源分解技术发展的多道信号处理方法,即是一种在只有观测数据且信号源混迭方法未知的情况下对信号独立源进行提取的一种信号处理方法。
    According to the properties that ICA can separate the underlying independent sources from the observed mixtures, P3 subcomponents are successfully extracted from the P3 complex.
    Traditional ICA aims to recover all independent source signals.
    Blind source separation (BSS) has been an active branch in signal processing field since 1990s. The specific advantage of BSS is that it can recover a set of unknown mutually independent source signals from their observed mixtures without knowing the source signals and the mixing coefficients.
    盲源分离(Blind Source Separation,BSS)是信号处理领域于20世纪90年代初发展起来的一个活跃分支,其特有优势在于能在各源信号和传输通道参数均未知的情况下,仅仅利用源信号的多个混合信号,就能够恢复源信号的各个独立成分。
    Blind Source Separation (BSS) is an approach to estimate and recover the independent source signals by using only the information within the mixtures observed at each input channel. One of the key issues in BSS is to develop the learning algorithm for the decomposition of matrices. Many approaches have been proposed to solve this problem, such as stochastic gradient algorithm based on information entropy method, natural gradient by maximum likelihood estimation based on information entropy method and so on.
    Blind source separation (BSS) is an emerging technique of array processing during the last twenty years. The aim of BSS is to recover the statistical independent source signals only from the observational signals without any knowledge of source signals and mixed channel. The process is also referred to as the independent component analysis (ICA).
    盲源分离(Blind Source Separation)是近二十年迅速发展起来的一种新兴技术,它在没有源信号与传输信道的任何先验知识的前提下,仅利用观测信号恢复出源信号。
    New theorems are presented which show how the location and the value of independent sources can be used in assessing whether or not a solution exists for the de equations of a very general class of nonlinear networks.
    By means of the method of node analysis,the controlled sources are usually transformed at first in such a way as to be similar to the independent sources, so that the networks possesses only two of the four forms.
    应用节点分析法时,一般先对受控源进行象独 立源一样的变换,使之只具有四种形式中的两种。
    On the basis of nature of source and resistance of dependent source, this paper introduces a systematic method transfering the active network(not contains independent source) to the passive network for calculating the equivalent resistance of one-port network with dependent source.
    The result shows : 1) In Liaohe deprssion basin, not only the depression can be an independent source system, but also each secondary depression in it can control the formation and accumulation of oil and gas.
    The anthor of the papar points out that.the linear network with controlled sources can be regarded as an independent source in case of adequate substitution for controlled sources, and it follows that its solution can be made directly by using linear network priuciple.


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