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Description: 一个可分解上万阶稀疏矩阵的SVD算法-a million bands on the sparse matrix of SVD algorithm
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Size: 31718 |
Author: 关 |
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Description: 一个可分解上万阶稀疏矩阵的SVD算法-a million bands on the sparse matrix of SVD algorithm
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Size: 364544 |
Author: 关 |
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Description: LAPACK是用Fortran90和规定套路解决系统同步线性方程组，最小二乘解线性方程组，特征值问题，以及奇异值问题。相关的矩阵分解（陆，乔莱斯基，快速反应，分解，舒尔，广义Schur ）也提供了，因为有关的计算，如重新安排的舒尔分解和估计条件号码。致密带状矩阵的处理，而不是一般稀疏矩阵。在所有领域，类似的功能是提供真正的和复杂的矩阵，在单，双精度-LAPACK is written in Fortran90 and provides routines for solving systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalue problems, and singular value problems. The associated matrix factorizations (LU, Cholesky, QR, SVD, Schur, generalized Schur) are also provided, as are related computations such as reordering of the Schur factorizations and estimating condition numbers. Dense and banded matrices are handled, but not general sparse matrices. In all areas, similar functionality is provided for real and complex matrices, in both single and double precision
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Size: 34160640 |
Author: Rocky |
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Size: 6256640 |
Author: 黎平 |
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Description: 有关稀疏矩阵的SVD算法（C语言版），非常有用，欢迎下载-The sparse matrix SVD algorithm (C language version)
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Size: 4096 |
Author: deng |
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Description: k-svd算法m代码.用于形成冗余字典，对图像进行稀疏分解-m k-svd algorithm code used to create a redundant dictionaries, sparse decomposition of images
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Size: 12544000 |
Author: 谢一天 |
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Description: K-SVD SPARSE REPRESENTATION 基于学习的稀疏表示图像分析方法，以去噪为例。-K-SVD SPARSE REPRESENTATION
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Size: 14626816 |
Author: 方小舞 |
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Description: 该算法是K-SVD算法的一种改进算法。该算法可以用于稀疏字典的学习中。与传统方法相比，能够有效的降低计算量，提高字典更新的速度。-The algorithm is an improved algorithm of K-SVD algorithm. The algorithm can be used to sparse dictionary learning. Compared with conventional methods, it is possible to effectively reduce the amount of computation, to improve the speed of dictionary update.
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Size: 3072 |
Author: Xu,J.P |
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Description: 数字图像处理，K-SVD字典学习方法，信号的稀疏与冗余表示理论，图像压缩，图像去噪-Digital image processing, K-SVD dictionary learning methods, sparse and redundant signal representation theory, image compression, image denoising
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Size: 6270976 |
Author: 李小落 |
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Description: 详细介绍了K-SVD字典训练的详细过程，对稀疏表示研究很有帮助.-Detailed introduces the K- SVD dictionary of detailed training process, the sparse say that research to have the help very much.
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Size: 763904 |
Author: duaiwanmei |
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Description: K-SVD同MOD一样也分为Sparse Coding和Dictionary Update两个步骤，Sparse Coding没有什么特殊的，也是固定过完备字典D，使用各种迭代算法求信号在字典上的稀疏系数。-K-SVD Sparse Coding and Dictionary Update is also divided into two steps, like MOD, Sparse Coding is not anything special, also fixed overcomplete dictionary D various iterative algorithms to find the signal on the dictionary sparse coefficient.
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Size: 12527616 |
Author: mqf |
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Description: 用于协同过滤推荐算法，svd矩阵分解算法 C++实现-Matrix Factorization , performs well on the large, sparse, and very imbalanced Netflix dataset
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Size: 11264 |
Author: liuyu |
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Description: KSVD算法，对于字典训练很实用，并且，对于基于稀疏表示方法，可以提高精度-KSVD algorithm for dictionary training is very practical，And, based on sparse representation method, can improve the precision
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Size: 769024 |
Author: wenwen li |
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Description: 内含用matlab编写的k-svd算法代码.可以对图像进行稀疏分解，另附ppt对ksvd进行理论学习-Includes using matlab k-svd algorithm code. Images can be sparse decomposition, attached ppt theoretical study of ksvd
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Size: 13321216 |
Author: 田 |
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Description: K-SVD算法用于稀疏表达,基于OMP算法。(The algorithm is apply for sparse representation)
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Size: 185344 |
Author: 长枪依在
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Description: 稀疏编码和字典学习算法，正交匹配追踪算法获得稀疏表示稀疏，ksvd用来学习字典(Sparse coding and dictionary learning algorithm, orthogonal matching tracking algorithm to obtain sparse sparse, ksvd used to learn the dictionary)
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Size: 4096 |
Author: 小敏敏1314
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Description: 通过字典学习更新的方法，对图像信号进行稀疏化分解(Through the method of learning and updating the dictionary, the image signals are sparse decomposed)
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Size: 486400 |
Author: smile北
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Description: 实现图像的稀疏编码，采用k-svd进行字典学习，omp算法进行稀疏表示系数的计算，内附有去噪例子(To achieve the image sparse coding, using K-SVD dictionary learning, OMP algorithm for sparse representation of the calculation of factors, with examples of denoising)
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Size: 2048 |
Author: chenchenchen...
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Description: K-SVD可以看做K-means的一种泛化形式，K-means算法总每个信号量只能用一个原子来近似表示，而K-SVD中每个信号是用多个原子的线性组合来表示的。
K-SVD通过构建字典来对数据进行稀疏表示，经常用于图像压缩、编码、分类等应用。(K-SVD can be regarded as a generalized form of K-means. The total K-means algorithm can only approximate one signal for each semaphore, and each signal in K-SVD is a linear combination of multiple atoms To express.
K-SVD through the construction of the dictionary to sparse data representation, often used for image compression, encoding, classification and other applications.)
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Size: 625664 |
Author: 华仔007
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Description: KSVD的稀疏编码去噪的matlab版本算法(Sparse encoding KSVD denoising algorithm)
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Size: 3072 |
Author: nirener0 |
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