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ncm

于 2014-02-14 发布 文件大小:270KB
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  numerical computing matthematics matlab

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  • biaozhunhua
    matlab环境下的程序对数据进行标准化,此程序简单易懂,效率也非常高,是一个非常好的程序代码,非常值得推荐!(matlab environment, the data standardization process, this process easy to understand, efficiency is very high, is a very good code, very recommendable!)
    2010-11-05 07:47:39下载
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  • T_w
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    2011-12-23 21:20:37下载
    积分:1
  • cuotout
    说明:  图像处理代码,能够对一张RGB图像类型的图片进行裁减,并且二值化处理。(Image processing code, capable of an RGB image types of pictures cut, and the binary treatment.)
    2010-03-22 23:25:45下载
    积分:1
  • v60-22
    This paper presents a new classification algorithm using colour and texture for obstacle detection. Colour information is computationally cheap to learn and process. However in many cases, colour alone does not provide enough information for classification. Texture information can improve classification performance but usually comes at an expensive cost.
    2010-05-13 07:13:53下载
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    2021-01-05 19:28:54下载
    积分:1
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    均值漂移跟踪算法的修改程序,包括源代码和调用程序。(Mean Shift tracking algorithm to modify the program, including source code and the calling program.)
    2013-11-25 21:03:40下载
    积分:1
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    2017-04-16 14:47:24下载
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    Matlab GUI程序, 带文件名browse功能,可打开excel文件。使用了listbox,edit,button等控件。 从excel文件中读取信息,显示在姓名和成绩两个窗口中,且可以在姓名窗口点选一个或多个姓名来显示对比成绩; 其中提供了文件浏览窗口,可供选取文件。 本例针对成绩文件score.xls,结构是:姓名,语文,数学,英语若干成绩。(Matlab GUI program with the file name browse function, can open the excel file. Use the listbox, edit, button, etc. controls. Read information from the excel file, name and achievements displayed in two windows, and you can name one or more of the window click on the name to display the comparison results which provides a file browser window, select the files available. In this case for the results file score.xls, the structure is: name, language, mathematics, English some success.)
    2010-06-04 01:17:00下载
    积分:1
  • linproj
    模型是结构体类型的线性投影Y = linproj(X, model) 其中W.model为线性投影矩阵, Y = model.W *X + model.b b为偏差值( Description: Y = linproj(X, model) linearly projects data in X such that Y = model.W *X+ model.b out_data = linproj(in_data, model) projects in_data.X out_data.X = model.W *in_data.X+ model.b out_data.y = in_data.y Input: model [struct] linear projection: .W [dim x ncomp] Projection matrix. .b [ncomp x 1] Bias.)
    2011-05-01 18:11:47下载
    积分:1
  • ofdm-tongbusuanfa
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    2016-04-27 08:09:35下载
    积分:1
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