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Block-TVNLR

于 2021-04-18 发布 文件大小:113KB
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下载积分: 1 下载次数: 10

代码说明:

  Image Compressive Sensing Recovery via Collaborative Sparsity

文件列表:

Block-TVNLR
...........\Demo.m,2879,2013-11-12
...........\House256.tif,66020,2012-11-07
...........\Readme.txt,792,2013-10-05
...........\Results
...........\Utilities
...........\.........\BCS_SPL_GenerateProjection.m,2221,2012-12-14
...........\.........\csnr.m,472,2010-08-13
...........\.........\defDDt.m,379,2009-02-19
...........\.........\f_handleA.m,703,2012-12-14
...........\.........\Toolbox_NLMeans
...........\.........\...............\image2vectors_double.c,12141,2010-04-28
...........\.........\...............\image2vectors_double.mexw32,20480,2012-07-20
...........\.........\...............\image2vectors_double.mexw64,13312,2013-07-02
...........\.........\...............\image2vectors_single.c,12162,2010-04-28
...........\.........\...............\image2vectors_single.mexw32,20480,2012-07-20
...........\.........\...............\image2vectors_single.mexw64,13824,2013-07-02
...........\.........\...............\license.txt,1335,2010-09-07
...........\.........\...............\NLMF.m,7207,2013-10-05
...........\.........\...............\NLMF2Dtree.m,3093,2013-10-05
...........\.........\...............\vectors_nlmeans_double.c,15772,2010-04-28
...........\.........\...............\vectors_nlmeans_double.mexw32,20480,2012-07-20
...........\.........\...............\vectors_nlmeans_double.mexw64,14336,2013-07-02
...........\.........\...............\vectors_nlmeans_single.c,15724,2010-04-28
...........\.........\...............\vectors_nlmeans_single.mexw32,20480,2012-07-20
...........\.........\...............\vectors_nlmeans_single.mexw64,14336,2013-07-02
...........\.........\TVNLR.m,18447,2013-10-04

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    复正弦的WVD;多个首尾相连的复正弦的WVD 一个实正弦的WVD(Complex sine the WVD both linked to a number of complex sinusoidal WVD of a real sinusoid of the WVD)
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    matlab方面有很多程序可以使用到学习与工作中(matlab, there are many programs you can use to learn and work)
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    神经网络训练根据Kolmogorov定理,输入层有14个节点,所以中间层有29个节点 %中间层神经元的传递函数为 tansig %输出层有8个节点,其神经元传递函数为logsig %训练函数采用traingdx(neural network training under the Kolmogorov theorem, input layer has 14 nodes, Therefore, the intermediate layer has 29% of nodes middle layer neurons in the transfer function for the output layer tansig% have eight nodes, its neuron transfer function for the training function logsig% used traingdx)
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