登录
首页 » matlab » K-SVD

K-SVD

于 2015-11-09 发布 文件大小:14122KB
0 206
下载积分: 1 下载次数: 9

代码说明:

  K-SVD是一种经典的字典训练算法,依据误差最小原则,对误差项进行SVD分解,选择使误差最小的分解项作为更新的字典原子和对应的原子系数,经过不断的迭代从而得到优化的解。(K-SVD is a classic dictionary training algorithm, based on the principle of minimum error, the error items SVD decomposition, choose to make the smallest error decomposition item as an updated dictionary of atoms and atomic corresponding coefficient, through constant iteration to obtain an optimized solution.)

文件列表:

K-SVD
.....\baocunmatwenjian.asv,815,2013-07-06
.....\baocunmatwenjian.m,815,2013-07-06
.....\BSyj_2.TIF,19426,2013-07-06
.....\CDS.asv,1890,2013-08-01
.....\CDS.m,1884,2013-08-01
.....\control_points_2eye_1mouth.mat,1335,2012-11-20
.....\expression_label_list.mat,250,2012-11-20
.....\file_name_list.mat,1540,2012-11-20
.....\findDistance.asv,1227,2013-07-10
.....\findDistance.m,1255,2013-07-10
.....\generate_list.asv,810,2013-07-10
.....\generate_list.m,824,2013-07-10
.....\generate_name_list.m,591,2013-07-10
.....\getim.asv,955,2013-07-06
.....\getim.m,955,2013-07-06
.....\getimage.m,1517,2013-07-06
.....\image37x30.mat,1783593,2013-07-10
.....\image50x40.mat,3212339,2013-07-10
.....\KA.AN1.39.tiff,14878,2012-11-20
.....\KA.AN2.40.tiff,14878,2012-11-20
.....\KA.AN3.41.tiff,14862,2012-11-20
.....\KA.DI1.42.tiff,14872,2012-11-20
.....\KA.DI2.43.tiff,14866,2012-11-20
.....\KA.DI3.44.tiff,14876,2012-11-20
.....\KA.FE1.45.tiff,14886,2012-11-20
.....\KA.FE2.46.tiff,14864,2012-11-20
.....\KA.FE3.47.tiff,14868,2012-11-20
.....\KA.FE4.48.tiff,14864,2012-11-20
.....\KA.HA1.29.tiff,14874,2012-11-20
.....\KA.HA2.30.tiff,14868,2012-11-20
.....\KA.HA3.31.tiff,14876,2012-11-20
.....\KA.HA4.32.tiff,14868,2012-11-20
.....\KA.NE1.26.tiff,14884,2012-11-20
.....\KA.NE2.27.tiff,14862,2012-11-20
.....\KA.NE3.28.tiff,14884,2012-11-20
.....\KA.SA1.33.tiff,14862,2012-11-20
.....\KA.SA2.34.tiff,14870,2012-11-20
.....\KA.SA3.35.tiff,14870,2012-11-20
.....\KA.SU1.36.tiff,14856,2012-11-20
.....\KA.SU2.37.tiff,14860,2012-11-20
.....\KA.SU3.38.tiff,14854,2012-11-20
.....\KL.AN1.167.tiff,14882,2012-11-20
.....\KL.AN2.168.tiff,14876,2012-11-20
.....\KL.AN3.169.tiff,14884,2012-11-20
.....\KL.DI1.170.tiff,14868,2012-11-20
.....\KL.DI2.171.tiff,14872,2012-11-20
.....\KL.DI3.172.tiff,14880,2012-11-20
.....\KL.DI4.173.tiff,14886,2012-11-20
.....\KL.FE1.174.tiff,14886,2012-11-20
.....\KL.FE2.175.tiff,14874,2012-11-20
.....\KL.FE3.176.tiff,14886,2012-11-20
.....\KL.HA1.158.tiff,14882,2012-11-20
.....\KL.HA2.159.tiff,14876,2012-11-20
.....\KL.HA3.160.tiff,14874,2012-11-20
.....\KL.NE1.155.tiff,14886,2012-11-20
.....\KL.NE2.156.tiff,14878,2012-11-20
.....\KL.NE3.157.tiff,14896,2012-11-20
.....\KL.SA1.161.tiff,14876,2012-11-20
.....\KL.SA2.162.tiff,14880,2012-11-20
.....\KL.SA3.163.tiff,14886,2012-11-20
.....\KL.SU1.164.tiff,14876,2012-11-20
.....\KL.SU2.165.tiff,14874,2012-11-20
.....\KL.SU3.166.tiff,14866,2012-11-20
.....\KM.AN1.17.tiff,14868,2012-11-20
.....\KM.AN2.18.tiff,14876,2012-11-20
.....\KM.AN3.19.tiff,14852,2012-11-20
.....\KM.DI1.20.tiff,14856,2012-11-20
.....\KM.DI3.22.tiff,14868,2012-11-20
.....\KM.FE1.23.tiff,14852,2012-11-20
.....\KM.FE2.24.tiff,14866,2012-11-20
.....\KM.FE3.25.tiff,14874,2012-11-20
.....\KM.HA1.4.tiff,14846,2012-11-20
.....\KM.HA2.5.tiff,14856,2012-11-20
.....\KM.HA3.6.tiff,14864,2012-11-20
.....\KM.HA4.7.tiff,14850,2012-11-20
.....\KM.NE1.1.tiff,14872,2012-11-20
.....\KM.NE2.2.tiff,14858,2012-11-20
.....\KM.NE3.3.tiff,14834,2012-11-20
.....\KM.SA1.9.tiff,14862,2012-11-20
.....\KM.SA2.10.tiff,14852,2012-11-20
.....\KM.SA3.11.tiff,14866,2012-11-20
.....\KM.SA5.13.tiff,14872,2012-11-20
.....\KM.SU1.14.tiff,14874,2012-11-20
.....\KM.SU2.15.tiff,14856,2012-11-20
.....\KM.SU3.16.tiff,14838,2012-11-20
.....\KR.AN1.83.tiff,14890,2012-11-20
.....\KR.AN2.84.tiff,14868,2012-11-20
.....\KR.AN3.85.tiff,14884,2012-11-20
.....\KR.DI1.86.tiff,14896,2012-11-20
.....\KR.DI2.87.tiff,14884,2012-11-20
.....\KR.DI3.88.tiff,14884,2012-11-20
.....\KR.FE1.89.tiff,14878,2012-11-20
.....\KR.FE2.90.tiff,14874,2012-11-20
.....\KR.FE3.91.tiff,14876,2012-11-20
.....\KR.HA1.74.tiff,14890,2012-11-20
.....\KR.HA2.75.tiff,14894,2012-11-20
.....\KR.HA3.79.tiff,14884,2012-11-20
.....\KR.NE1.71.tiff,14900,2012-11-20
.....\KR.NE2.72.tiff,14898,2012-11-20

下载说明:请别用迅雷下载,失败请重下,重下不扣分!

发表评论

0 个回复

  • demodulation
    后续的接调制的程序,跟以前传的调制是在同样的环境下实现的(Follow-up modem access procedures, with the previous Chuan modulation is in the same environment to achieve)
    2008-05-03 08:28:35下载
    积分:1
  • Resonance-freq
    Resonance frequency-1D cavity FDTD(Fast fourier transform)Numeric-analytic-electromagnetic
    2013-07-12 04:36:01下载
    积分:1
  • eg14-zhishupince
    《MATLAB神经网络30个案例分析》中的第14个例子,案例14 SVM神经网络的回归预测分析---上证开盘指数预测。希望对大家有一定的帮助!(The MATLAB neural network analysis of 30 cases of example, 14 cases (14 of SVM neural network predictive regression analysis- Shanghai opened index prediction. Hope to have certain help to everybody! )
    2013-09-20 16:29:53下载
    积分:1
  • bpAnn
    说明:  利用物体的几何特征参数,和bp神经网络实现分类。(The use of the geometric characteristics of object parameters, and the realization of bp neural network classification.)
    2009-07-30 10:58:09下载
    积分:1
  • split
    城市交通方式划分,运用于城市轨道交通需求预测(Traffic cell Od merging process, applied to urban rail transport demand forecast)
    2011-07-14 15:35:30下载
    积分:1
  • BER-simulation-for-BPSK-with-AWGN
    With this matlab codes one can simulate BER for BPSK Modulation with added noise in various steps
    2014-02-20 19:40:31下载
    积分:1
  • Fundamentals_of_Signals_and_Systems
    this is very good book for signals and systems
    2010-09-15 15:50:51下载
    积分:1
  • matlab
    本书是基于Matlab6.5的优化工具箱v2.2编写的。书中全面系统地介绍了优化方法的基础理论和优化工具箱v2.2函数的功能、语法和工程实际应用。全书侧重于优化工具箱在工程中的具体应用,通过具体的分析和详细的实例,读者不仅能对Matlab优化工具箱函数的强大功能与一个深刻的了解,更能学会正确运用优化工具箱函数快速解决实际问题,从而提高分析问题和解决问题的能力(This book is based on the optimization toolbox v2.2 Matlab6.5 prepared. The book introduces a comprehensive and systematic optimization approach is based on theory and optimization toolbox v2.2 of functionality, syntax and engineering applications. The book focuses on the optimization toolbox of specific applications in engineering, analysis and detail through specific examples, the reader not only to the Matlab optimization toolbox function power and a profound understanding, better learn to correctly use the fast optimization toolbox function solve practical problems, thereby improving analysis of problems and problem-solving ability)
    2011-01-14 14:46:55下载
    积分:1
  • Paper4-(1)
    Applying postureidentifierindesigninganadaptivenonlinearpredictive controller fornonholonomicmobilerobot
    2015-01-06 04:57:39下载
    积分:1
  • edison
    edge detection for plate recognition
    2012-01-14 06:26:42下载
    积分:1
  • 696518资源总数
  • 106253会员总数
  • 14今日下载