<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Eigenvectors on Chen Kai Blog</title><link>https://www.chenk.top/en/tags/eigenvectors/</link><description>Recent content in Eigenvectors on Chen Kai Blog</description><generator>Hugo</generator><language>en</language><lastBuildDate>Wed, 05 Feb 2025 09:00:00 +0000</lastBuildDate><atom:link href="https://www.chenk.top/en/tags/eigenvectors/index.xml" rel="self" type="application/rss+xml"/><item><title>Essence of Linear Algebra (6): Eigenvalues and Eigenvectors</title><link>https://www.chenk.top/en/linear-algebra/06-eigenvalues-and-eigenvectors/</link><pubDate>Wed, 05 Feb 2025 09:00:00 +0000</pubDate><guid>https://www.chenk.top/en/linear-algebra/06-eigenvalues-and-eigenvectors/</guid><description>&lt;p>&lt;figure class="article-figure">
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&lt;h2 id="the-big-question" class="heading-anchor">The Big Question&lt;a href="#the-big-question" class="heading-link" aria-label="Permalink to this section" title="Copy link to this section">#&lt;/a>
&lt;/h2>&lt;p>Apply a matrix to a vector and almost anything can happen. Most vectors get rotated &lt;em>and&lt;/em> stretched, landing in a brand new direction. But scattered among them are a few special vectors that refuse to leave their span. They come out of the transformation pointing exactly the way they went in — only longer, shorter, or flipped.&lt;/p></description></item></channel></rss>