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这是CISS会议上发表的著名论文“Tensor Canonical decomposition based method for blind identification of MIMO system with 3-input 2-output case”的源程序,主要是讲基于张量规范分解的多天线系统的忙识别问题,里边包含了相应的文章,可以一起对照着看。-conference on the famous treatise "Tensor Canonical deco mposition
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基于特征函数的张量分解相关代码,结合“lm”,“als”等很多算法。
主要用于处理欠定MIMO系统识别-Based on the characteristic function of the tensor decomposition of the relevant code, combined with the " lm" , " als" and many other algorithms. Mainly used for underdetermined
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张量工具箱,提供张量分解等功能,附上安装说明文件,经测试很好用。-tensor decomposition and install readme
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张量分解程序,支持平行因子分解模型和TUCKER分解模型-Tensor decomposition process, and support for parallel factorization model and TUCKER decomposition model
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在VC++开发平台下,基于OPenGl开发包实现绘图功能,完成点云数据的绘制后,通过张量分解实现特征点检测-In VC++ development platform, based on the OPenGl development kit graphics, drawing completion point cloud data, through the tensor decomposition to achieve feature point detection
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离散小波变换域非负张量分解的高光谱遥感图像压缩-Discrete wavelet transform domain of non-negative tensor decomposition of hyperspectral remote sensing image compression
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Fast algorithm for higher order CANDECOMP/PARAFAC tensor decomposition
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toolbox for tensor decomposition in Matlab
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着重研究三阶非负张量分解问题,回顾三阶张量的非负分解模
型(NTVl,阐述了算法的思想及实现过程。接着,从张量投影的角度出发,建
立了基于张量投影的非负分解模型(NTPM),阐述了模型的想法,并给出了相
应的算法公式。-Nonnegative tensor decomposition and application
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张量分析基础,理论方面的参考书籍,张量是与坐标系有联系的一组量,并满足一定的坐标变换规律。-Nonnegative tensor decomposition and application
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Channel Estimation for Millimeter Wave MIMO-OFDM Systems via Low-Rank Tensor Decomposition
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利用SVD实现item-based CF:
优点: 简化数据,去除噪声,提高算法的结果
缺点: 数据的转换可能难以理解
适用数据类型: 数值型数据(Svd decomposition plays an important role in the decomposition of eigenvalues of high-dimensional data, while using low-dimensional data for approximate approximation)
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use the swift method to make impedance tensor decomposition
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plot the result of impedance tensor decomposition
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基于张量Tucker分解的数据修复算法,能对缺失数据修复(Data repair algorithm based on tensor decomposition)
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非负矩阵重构图像,用lena图片重构效果还行(All the documents of tensor decomposition)
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介绍张量分解的基本原理和应用,力求在广度和深度方面都有所兼顾,这是以往类似的文章所没有做到的。这篇综述性质的文章旨在为研究人员和初学者提供一个良好的开端,让研究人员有兴趣使用张量运算来解决问题。(This paper introduces the basic principles and applications of tensor decomposition, and strives to give consideration to both breadth and depth, which
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一种张量分解的算法,应用于盲源分离和机器学习。(An algorithm for tensor decomposition)
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整合了不完整张量的平滑平行因子分解和最小化张量秩模型的有效选择的张量补全,用于图像处理,(The proposed method admits significant advantages, owing to the integration of smooth PARAFAC decomposition for incomplete tensors and the efficient selection of models in order to minimize the tensor rank
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一些关于张量填充,张量恢复,张量分解的一些常用算法(CP分解,Tucker分解)(some Algoithm about tensor decomposition)
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