Description: 宽带信号 DOA估计 TCT算法 此算法可以较好的完成宽带信号的波达角估计 可以解相干信号 属于子空间算法-Wideband signal DOA estimates TCT algorithm this algorithm can better complete the broadband signal can be solution-of-arrival estimation of coherent signals are sub-space algorithm Platform: |
Size: 2048 |
Author:金江 |
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Description: 此算法为基于最大似然方法的DOA估计 是区别于子空间类的DOA算法 但需要多维搜索 计算量较大-This algorithm is based on the maximum likelihood method of DOA estimation is different from the sub-space kind of DOA algorithm but calculating the volume of the larger multi-dimensional search Platform: |
Size: 1024 |
Author:金江 |
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Description: 人脸识别的matlab代码，本征脸（ eigenface ）方法是子空间人脸识别方法的典型代表。该方法基于一种部分的K-L 变换，或者称为主成分分析（ PCA ）-Matlab code for face recognition, eigenface (eigenface) sub-space method is a typical representative of face recognition methods. The method is based on a part of the KL transform, or known as principal component analysis (PCA) Platform: |
Size: 1024 |
Author:李英豪 |
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Description: 实现信号的KDDA映射变换，KDDA属于线性子空间分析方法LDA的改进算法，采用核方法实现映射-Realize signal KDDA mapping transformation, KDDA belonging to a linear sub-space analysis method to improve the LDA algorithm, use of the mapping method Platform: |
Size: 6144 |
Author:loujun |
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Description: 子空间的出现使模式识别有了突破性的发展，而特征提取则是子空间实现的一个重要环节，提取特征的好坏决定了子空间方法的成功与否-The emergence of sub-space to make a breakthrough with the development of pattern recognition, and feature extraction is a sub-space realization of an important link, extract the characteristics of good and bad decisions of the sub-space method of the success of Platform: |
Size: 494592 |
Author:lulu |
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Description: 利用Sub-pattern PCA在Yale人脸库上进行人脸识别的matlab源代码，子模式主成分分析首先对原始图像分块，然后对相同位置的子图像分别建立子图像集，在每一个子图像集内使用PCA方法提取特征，建立子空间。对待识别图像，经相同分块后，分别将子图像向对应的子空间投影，提取特征。最后根据最近邻原则进行分类。-Sub-pattern PCA use in the Yale face database for face recognition on the matlab source code, sub-mode principal component analysis first of the original image block, and then the same sub-image, respectively, the location of the establishment of sub-image set, in each sub-image Set the use of PCA to extract the features, the establishment of sub-space. Treatment to identify images, by the same block, the respective sub-image to the corresponding sub-space projection, feature extraction. Finally, according to the principle of nearest neighbor classification. Platform: |
Size: 2048 |
Author:章格 |
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Description: 该程序是子空间在盲点估计的应用，开发环境是MATLAB，对学习子空间辨识算法的很有用！-The program is estimated that sub-space in the blind spot of the application development environment is MATLAB, on learning subspace identification algorithm is useful! Platform: |
Size: 2048 |
Author:李昊 |
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Description: 基于非负矩阵分解（NMF）的人脸特征提取算法，NMF基本思想是找到一个线性子空间W，使的构成子空间的基本图像的像素点都是正值，而且人脸图像在子空间上的投影系数也是正数-Non-negative Matrix Factorization (NMF) of facial feature extraction algorithm, NMF basic idea is to find a linear sub-space W, so that the composition of sub-space of the basic image pixels are positive, and face image in the sub-space projection coefficient is positive Platform: |
Size: 1024 |
Author:李伟 |
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Description: 线性判别分析法（LDA），LDA以提高样本在子空间中的可分类为目标。寻找一组基向量，在这些基向量张成的子空间中，不同类别的训练样本能有最小的类内离散度，最大的类间离散度。-Linear discriminant analysis (LDA), LDA in order to improve the sample in the sub-space can be classified as a target. Find a group-based vector, vector-based Zhang in these sub-space, different types of training samples can have the smallest dispersion category, the largest between-class dispersion. Platform: |
Size: 1024 |
Author:李伟 |
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Description: music算法的实现 MU S IC 算法是一种子空间分解算法, 它的各种性能已被广泛研究. 在信号波达方向估计领
域, MU S IC 算法的应用, 形成了MU S IC 波达方向估计算法. 实际应用中,MU S IC 波达方向估计算法, 拥有超分辨能力的同时, 也存在原理性缺点——MU S IC 空间谱不能反映目标信号的相对强度. 文中在前人工作的基础上, 对MU S IC 波达方向估计算法进行理论分析, 提出了有效的改进方法, 并通过仿真试验证实了分析的正确性.
-music algorithm MU S IC algorithm is a sub-space decomposition method, its performance has been extensively studied. In the field of signal DOA estimation, MU S IC algorithm applications, MU S IC formed DOA estimation algorithm . practical application, MU S IC DOA estimation algorithm, with super-resolution capacity, but also the existence of the principle of sexual shortcomings- MU S IC space spectrum do not reflect the relative strength of the target signal. text in the work of our predecessors on the basis of MU S IC on DOA estimation algorithm theoretical analysis, an effective method to improve and, through simulation analysis confirmed the correctness. Platform: |
Size: 1024 |
Author:wudi |
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Description: 子模式主成分分析首先对原始图像分块，然后对相同位置的子图像分别建立子图像集，在每一个子图像集内使用PCA方法提取特征，建立子空间。对待识别图像，经相同分块后，分别将子图像向对应的子空间投影，提取特征。最后根据最近邻原则进行分类。-Sub-mode principal component analysis first of the original image block, and then the same sub-image, respectively, the location of the establishment of sub-image set, in each sub-image set to use PCA to extract the features, the establishment of sub-space. Treatment to identify images, by the same block, the respective sub-image to the corresponding sub-space projection, feature extraction. Finally, according to the principle of nearest neighbor classification. Platform: |
Size: 165888 |
Author:tanghui |
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Description: 该程序是基于子空间的语音去噪声,该方法使用广泛,能取得很好的语音增强效果!-The program is based on the sub-space of the voice to noise, the method widely used and can achieve very good speech enhancement effect! Platform: |
Size: 1024 |
Author:zhjuna |
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Description: 本文介绍了子空间模型辨识的多种方法，并对其不同的方法进行了综合的分析，研究，比较。-This paper introduces the sub-space model identification of a number of ways, and different ways to carry out a comprehensive analysis, research, compare. Platform: |
Size: 375808 |
Author:张林 |
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Description: 擅 蔓：以人脸的表情识别为实验背景， 分析了在对人脸表情的识别过程中，单个独立分薰对识别率的影响，由此进一步总结了在表情识
别中如何更有效地选取独立子空间，以实现在不影响识别率的前提下，减少用于构成独立子空问所需的独立分量的个数。 独立成分分析；表情识别；独立子空间 -Good man: Face to face identification for the experimental background, the analysis of facial expressions in the identification process, a single smoked separate the impact of the recognition rate, thus further summarized in the expression recognition of how to more effectively select the independent sub-space in order to achieve the recognition rate does not affect the premise, for constituting a separate sub-reducing space required for the number of independent component. Independent component analysis expression recognition independent subspace Platform: |
Size: 272384 |
Author:金振东 |
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Description: 图像在传输过程中，传递函数对高频成分有衰减作用，造成图像模糊，细节轮廓不清楚。图像锐化就是补偿图像的轮廓，增强图像的边缘及灰度跳变的部分，使图像变得清晰。亦分空域处理和频域处理两类[3]。-Image in the transmission process, the transfer function of the role of high frequency components are attenuated, resulting in image blurring, the details of the outline is not clear. Image sharpening is the outline of the image compensation, edge enhancement and gray-scale image of the hopping part of the image became clear. Also sub-space and frequency domain processing to deal with two types of [3]. Platform: |
Size: 171008 |
Author:王瑜 |
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Description: 非负矩阵分解法，这一种新型的子空间分解方法，增加了非负性约束，比PCA、ICA更有效-Non-negative matrix factorization method, which a new type of sub-space decomposition method, an increase of non-negative constraint, compared with PCA, ICA is more efficient Platform: |
Size: 1024 |
Author:刘文娅 |
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