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用最大相似性方法实现独立分量分析算法的matlab代码，可用于盲信号处理和图像滤波器构造。-with the greatest similarity method independent component analysis algorithm Matlab code can be used to blind signal processing and image filter structure.
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独立分量分析（maltab代码）用于图象处理得方法-independent component analysis (maltab code) used in image processing methods
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Matlab环境下的基于独立分量分析（ICA）算法的图像混合与分离仿真程序．-Matlab environment based on the independent component analysis (ICA) algorithm for image simulation mixed with the separation process sequence.
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Kernel Independent Component Analysis.这是核独立元分析的源程序
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独立分量分析 方法 压缩 与 解压 图像。 MATLAB 实现，有测试平台。,Independent Component Analysis image compression and decompression. MATLAB realization of a test platform.
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独立分量分析的算法，用于分离出独立分量，用于图像降维，特征提取-Independent component analysis algorithms, used to separate out the independent component for the image dimensionality reduction, feature extraction
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一种基于ICA的多源图像融合算法为了尽可能
达到这一要求，在分析盲源分离理论的基础上，提出了一种基于独立分量分析(ICA)的图像融合算法。-ICA-based multi-source image fusion algorithm in order to meet this requirement as far as possible, in the analysis of blind source separation based on the theory put forward bas
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独立分量分析ICA，用于图像处理，程序不错，可以参考-Independent Component Analysis ICA, for image processing, the procedure well, can refer to
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：由于许多传统的去噪方法在强背景噪声情况下提取声音信号的能力变弱甚至失效， 提出
应用独立成分分析( I C A) 方法对声音信号进行特征提取， 并证明了这种 I C A 变换能增强语音和音
乐信号的超高斯性． 在此基础上， 应用 I C A基函数作为滤波器， 通过阈值化的去噪方法对含有强高
斯背景噪声的声音信号进行去噪仿真实验． 结果表明， 本方法明显优于传统的均值滤波和小波去噪
方法， 为强背景噪声下弱信号的检测提供 了新的途径．-: As many of the t
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ica 核独立主元分析（kernel independent component analysis)软件包-kica
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The relative usefulness of Independent
Component Analysis (ICA) for Face Recognition is described.
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醫學影像處理實驗-Independent component analysis of mixed music files學習如何使用 ICA，分離出音樂檔案的主旋律及和音樂-Independent component analysis of mixed music files
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MATLAB医学影像处理实验(内含14个原代码及教学的说明)
(1)Plot a sine function using MATLAB, and write the data into a file
(2)Read data from a file, plot a SINC function, and append the result back to the same file
(3)Plot a Gaussian distribution using MATLAB
(4)Fo
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本文首先概述了独立成分分析与盲信号分离， 主成分分析的关系， 然后系统地介绍了该技术的基本概念和数据模型， 对现今比较流行的各种独立成分分析算法进行了剖析和总结。最后对独立成分分析的发展及应用前景作了展望-In this paper, an overview of independent component analysis and blind signal separation, principal component analysis of the relationship, and the
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fast fixed-point algorithm -The FastICA package is a free (GPL) MATLAB program that implements the fast fixed-point algorithm for independent component analysis and projection pursuit. It features an easy-to-use graphical user interface, and a comput
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特征提取是模式识别研究领域的一个热点.本文提出了一种基于独立成分分析和线性鉴别分析的特征提取方法.谊方法中引入了零空间的概念,指出了前人算法中的不足之,并且给出了一个完整的独立成分分析和线性鉴别分析的组合算法.在ORL和Yale人脸数据库上的实验表明了该方法的有效性.-Feature extraction is a hot field of pattern recognition research. In this paper, which is based on independent com
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基于快速独立分量分析盲复原算法的混合图像分离-Independent component analysis based on fast recovery algorithm for blind separation of mixed images
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此工具包包含实现独立成分分析的若干matlab程序-The kernel-ica package is a Matlab program that implements the Kernel
ICA algorithm for independent component analysis (ICA).
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本程序主要用于基于ica独立分量分析，主要利用ica提取图像的特征-This procedure is mainly used for ica-based independent component analysis, the main use of the image feature extraction ica
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基于独立分量分析的图像特征提取及泊松噪声去除，用于初学者，很实用，欢迎下载-Independent component analysis based on image feature extraction and removal of Poisson noise, for beginners, it is useful, please download
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