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  1. compressive sensing l1 norm

  2. 求解L1范数的有效方法。是从Donoho那里出来的，有论文和源码。

  3. 所属分类：专业指导

    • 发布日期：2010-02-18
    • 文件大小：1048576
    • 提供者：yuyibintony

  1. occam一维反演

  2. C----------------------------------------------------------------------- program runocc C----------------------------------------------------------------------- c C OCCAM 2.0: Steven Constable IGPP/SIO La Jolla CA 92093-0225 c Program Revision 2.01,

  3. 所属分类：其它

    • 发布日期：2013-04-21
    • 文件大小：56320
    • 提供者：u010380504

  1. L1-norm Minimization

  2. 一份介绍L1-norm Minimization很好的文档

  3. 所属分类：专业指导

    • 发布日期：2013-06-20
    • 文件大小：2097152
    • 提供者：u011143461

  1. Fast and Robust Multi-Frame Super-Resolution

  2. This paper propose an alternate approach using L1 norm minimization and robust regularization based on a bilateral prior to deal with different data and noise models.

  3. 所属分类：其它

    • 发布日期：2014-02-28
    • 文件大小：5242880
    • 提供者：zhaoxunjie

  1. Low-Rank Modeling of Local k-Space Neighborhoods (LORAKS) for Constrained MRI

  2. Recent theoretical results on low-rank matrix reconstruction have inspired significant interest in low-rank modeling of MRI images. Existing approaches have focused on higher-dimensional scenarios with data available from multiple channels, timepoin

  3. 所属分类：其它

    • 发布日期：2015-12-27
    • 文件大小：2097152
    • 提供者：zhangmh3529

  1. Introduction_to_Optimum_Design.pdf

  2. Preface ix Chapter 1 Introduction to Design 1 1.1 The Design Process 2 1.2 Engineering Design versus Engineering Analysis 4 1.3 Conventional versus Optimum Design Process 4 1.4 Optimum Design versus Optimal Control 6 1.5 Basic Terminology and Notati

  3. 所属分类：Java

    • 发布日期：2008-11-18
    • 文件大小：4194304
    • 提供者：xfwhj

  1. TVDENOISE.m

  2. % u = TVDENOISE(f,lambda) denoises the input image f. The smaller % the parameter lambda, the stronger the denoising. % % The output u approximately minimizes the Rudin-Osher-Fatemi (ROF) % denoising model % % Min TV(u) + lambda/2 || f - u ||^2_2, %

  3. 所属分类：其它

    • 发布日期：2009-03-22
    • 文件大小：3072
    • 提供者：biaoge12345

  1. 加权的核函数最小化程序

  2. 作为低秩矩阵逼近在图像处理中具有广泛的应用，其目的是根据退化图像的自相似性得到低秩矩阵来对图像进行去噪，如在计算机视觉和机器学习.低秩矩阵近似方法一般可分为两类，低秩矩阵分解(LowＲank Matrix Factorization，LＲMF)方法和核范数最小化(Nuclear Norm Minimization，NNM)方法。

  3. 所属分类：专业指导

    • 发布日期：2018-07-11
    • 文件大小：48128
    • 提供者：qq_38648917

  1. Multi-channel Weighted Nuclear Norm Minimization for Real Color Image Denoising

  2. 《多通道加权核范数最小化用于实际彩色图像去噪》 《Multi-channel Weighted Nuclear Norm Minimization for Real Color Image Denoising》 该论文的matlab代码，仅供研究学习。 具体看readme。

  3. 所属分类：机器学习

    • 发布日期：2019-05-10
    • 文件大小：25600
    • 提供者：sinat_29250497

  1. Matrix factorization for multivariate time series analysis

  2. Matrix factorization is a powerful data analysis tool. It has been used in multivariate time series analysis, leading to the decomposition of the series in a small set of latent factors. However, little is known on the statistical performances of mat

  3. 所属分类：机器学习

    • 发布日期：2019-03-16
    • 文件大小：294912
    • 提供者：lex_glimmer

  1. Denoising 3-D magnitude magnetic resonance images based on weighted nuclear norm minimization

  2. A new denoising algorithm based on low-rank matrix approximation (LRMA) with regularization of weighted nuclear norm minimization (WNNM) is proposed to remove Rician noise of magnetic resonance (MR) images. This technique simply groups similar non-lo

  3. 所属分类：其它

    • 发布日期：2021-02-22
    • 文件大小：3145728
    • 提供者：weixin_38707356

  1. 07_A Generalized Norm Minimization Approach for Distributed Estimation in Sensor Networks

  2. 07_A Generalized Norm Minimization Approach for Distributed Estimation in Sensor Networks

  3. 所属分类：其它

    • 发布日期：2021-02-21
    • 文件大小：202752
    • 提供者：weixin_38702110

  1. Face recognition by sparse discriminant analysis via joint L2,1 norm minimization

  2. Recently, joint feature selection and subspace learning, which can perform feature selection and subspace learning simultaneously, is proposed and has encouraging ability on face recognition. In the literature, a framework of utilizing L-2,L-1-norm p

  3. 所属分类：其它

    • 发布日期：2021-02-10
    • 文件大小：513024
    • 提供者：weixin_38577922

  1. Fast Hessian Frobenius Norm Based Image Restoration

  2. A projected gradient algorithm (PGA) which is derived from the majorization-minimization (MM) framework has been proposed recently for Hessian-matrix Frobenius norm regularization image restoration model so that it currently p

  3. 所属分类：其它

    • 发布日期：2021-02-09
    • 文件大小：431104
    • 提供者：weixin_38686399

  1. Array covariance matrix-based atomic norm minimization for off-grid coherent direction-of-arrival estimation

  2. Array covariance matrix-based atomic norm minimization for off-grid coherent direction-of-arrival estimation

  3. 所属分类：其它

    • 发布日期：2021-02-07
    • 文件大小：811008
    • 提供者：weixin_38747025