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index.html
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<!DOCTYPE html>
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and open the template in the editor.
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<html>
<head>
<title>CN Delivery 1</title>
<link rel="shortcut icon" href="favicon.ico" >
<link rel="icon" href="obrasinf.gif" type="image/gif" >
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
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<body>
<div>
<h1>
Complex Networks
</h1>
<p>
Statement
</p>
<p>
<a href="pages/barbasian.html">
a) Generation of networks using the Barabasi & Albert preferential attachment model.
</a>
Compute the degree distribution and the complementary cumulative degree distribution, using histograms in log scale.
Fitting of the power-law exponent from the histograms, and using the maximum likelihood estimation (MLE) as it appears in Newman's review.
Build networks of different sizes (from 1000 to 100000 nodes), and with different average degree (2, 4, 6, ...).
<br>
<a href="pages/report.html">
REPORT.
</a>
</p>
<!--
<p>
<a href="pages/configuration.html">
b) Implementation of the Configuration Model.
</a>
Generate networks of different sizes following Poisson degree distributions (Erdos-Renyi) and power-law degree distributions with different exponents (2.2, 2.5, 2.7).
For the latter, calculate the exponents as in exercise 1a.
</p>
-->
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</body>
</html>