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psnr_nmse_rms

于 2015-10-29 发布文件大小:5KB

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下载积分: 1 下载次数: 9

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代码说明：

通过matlab编写的几个关于PSNR、mse的图像处理的小程序(Several small program written by matlab about PSNR, mse image processing)

文件列表：

通过matlab编写的几个关于PSNR、mse的图像处理的小程序psnr_nmse_rms
................................................................\通过matlab编写的几个关于PSNR、mse的图像处理的小程序psnr_nmse_rms
................................................................\................................................................\NMSE.m,741,2015-10-29
................................................................\................................................................\NMSE.rar,465,2015-10-29
................................................................\................................................................\psnr.m,994,2006-10-27
................................................................\................................................................\psnr.rar,549,2015-10-29
................................................................\................................................................\RMS.m,1078,2006-10-27
................................................................\................................................................\RMS.rar,583,2015-10-29

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2008-09-17 22:03:10下载

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2014-10-10 22:23:10下载

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RNNSIM v.2 package contains a number of m-files for training and evaluation of the random neural network. All functions have been thoroughly tested. After downloading the separate files or the zipped file, make sure that they are stored or extracted in the directory /rnnsimv2 Below an overview of the files contained in this directory along with a brief description of what they do. The on-line help facility explains how to call the different functions. You simply write help <function-name> in the MATLAB command window. Along with the m-files in this directory you will find a manual for the simulator in PDF format (rnnsimv2.pdf). Start by printing this out and read the release notes. Two simple demonstration programs are given to illustrate how most of the functions work.

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threshold for sparse approximation

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2011-10-23 12:50:53下载

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2006-11-12 20:45:49下载

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