mhjensen
159 lines
5.1 KiB
HTML
159 lines
5.1 KiB
HTML
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<title>Data Analysis and Machine Learning: Recurrent neural networks</title>
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<a class="navbar-brand" href="Recurrent-bs.html">Data Analysis and Machine Learning: Recurrent neural networks</a>
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<!-- navigation toc: --> <li><a href="._Recurrent-bs001.html#___sec0" style="font-size: 80%;">Recurrent neural networks: Overarching view</a></li>
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<!-- navigation toc: --> <li><a href="._Recurrent-bs002.html#___sec1" style="font-size: 80%;">Set up of an RNN</a></li>
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<!-- navigation toc: --> <li><a href="#___sec2" style="font-size: 80%;">Solving differential equations and eigenvalue problems with RNNs</a></li>
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<h2 id="___sec2" class="anchor">Solving differential equations and eigenvalue problems with RNNs </h2>
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<p>
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In our discussions of ordinary differential equations and partial
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differential equations using neural networks. Here we will discuss how
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we can solve say ordinary differential equations and eigenvalue
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problems using RNNs. Eigenvalue problems can be solved using RNNs by
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rewriting such a problems as a non-linear differential equation.
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<p>
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Instead of starting with a well-known ordinary differential equation,
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we start directly with an eigenvaule problem.
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<li><a href="._Recurrent-bs002.html">«</a></li>
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<li><a href="._Recurrent-bs000.html">1</a></li>
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<li><a href="._Recurrent-bs001.html">2</a></li>
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<li><a href="._Recurrent-bs002.html">3</a></li>
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<li class="active"><a href="._Recurrent-bs003.html">4</a></li>
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<li><a href="._Recurrent-bs004.html">5</a></li>
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