<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Matlab on 桑峰</title><link>https://isangfeng.github.io/tags/matlab/</link><description>Recent content in Matlab on 桑峰</description><generator>Hugo -- gohugo.io</generator><language>zh-cn</language><copyright>© 2026 桑峰</copyright><lastBuildDate>Thu, 25 May 2023 00:00:00 +0000</lastBuildDate><atom:link href="https://isangfeng.github.io/tags/matlab/index.xml" rel="self" type="application/rss+xml"/><item><title>周总结-数据转换</title><link>https://isangfeng.github.io/posts/2023/05/weeklynotes21/</link><pubDate>Thu, 25 May 2023 00:00:00 +0000</pubDate><guid>https://isangfeng.github.io/posts/2023/05/weeklynotes21/</guid><description>&lt;h2 class="relative group"&gt;转换数据
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&lt;p&gt;问题：假设有两组数据X和Y，要求转换Y，使得转换后的Y曲线下面积与X的曲线下面积相同。&lt;/p&gt;</description></item><item><title>典型相关分析CCA</title><link>https://isangfeng.github.io/posts/2023/05/practiceaboutcca/</link><pubDate>Wed, 10 May 2023 00:00:00 +0000</pubDate><guid>https://isangfeng.github.io/posts/2023/05/practiceaboutcca/</guid><description>&lt;p&gt;典型相关分析（Canonical Correlation Analysis, CCA）可以计算两组变量（每组变量包含多个变量）之间的相关。参考Pearson相关，它只能计算两个变量之间的相关。本文主要介绍笔者在使用CCA的过程中的理解，可能存在不准确的地方。详细的原理，请参考：&lt;a href="https://www.cnblogs.com/pinard/p/6288716.html" target="_blank" rel="noreferrer"&gt;https://www.cnblogs.com/pinard/p/6288716.html&lt;/a&gt;。&lt;/p&gt;</description></item><item><title>CIFTI文件的读取和可视化</title><link>https://isangfeng.github.io/posts/2022/2022-02-22-readcifti/</link><pubDate>Tue, 22 Feb 2022 00:00:00 +0000</pubDate><guid>https://isangfeng.github.io/posts/2022/2022-02-22-readcifti/</guid><description>&lt;p&gt;CIFTI (Connectivity Informatics Technology Initiative) 是HCP项目中开发的神经影像存储格式。具体可参考2016年Glasser等人发表的文章(Glasser et al., Nature neuroscience, 2015)。开发者在GitHub上提供了读写的MATLAB工具包，可在此处下载：https://github.com/Washington-University/cifti-matlab。&lt;/p&gt;</description></item><item><title>Singularity-05-Matlab&amp;fmriprep</title><link>https://isangfeng.github.io/posts/2022/2022-02-21-singularity5/</link><pubDate>Mon, 21 Feb 2022 00:00:00 +0000</pubDate><guid>https://isangfeng.github.io/posts/2022/2022-02-21-singularity5/</guid><description>&lt;h2 class="relative group"&gt;运行MATLAB
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&lt;p&gt;使用matlab镜像运行matlab可使用如下命令：&lt;/p&gt;</description></item><item><title>Singularity-04-安装MATLAB</title><link>https://isangfeng.github.io/posts/2022/2022-02-17-singularity4/</link><pubDate>Thu, 17 Feb 2022 00:00:00 +0000</pubDate><guid>https://isangfeng.github.io/posts/2022/2022-02-17-singularity4/</guid><description>&lt;p&gt;以下是记录本人在使用学院高性能计算平台运行singularity中遇到的问题以及相应的解决方法，不一定适用于其他场景。&lt;/p&gt;</description></item></channel></rss>