<?xml version="1.0" encoding="UTF-8" ?>
<?xml-stylesheet type="text/xsl" href="https://ez.analog.com/cfs-file/__key/system/syndication/rss.xsl" media="screen"?><rss version="2.0" xmlns:dc="http://purl.org/dc/elements/1.1/"><channel><title>Deep Learning for Radio Frequency Systems</title><link>https://ez.analog.com/webinar/c/e/117</link><description>&lt;p&gt;&lt;span&gt;Deep learning within RF shows promise for dealing with a congested spectrum by enhancing reliability and simplifying the task of building wireless systems. In this webinar we will discuss a software defined radio that can perform real-time DSP and deep learning with an NVIDIA GPU and an Analog Devices front end. We'll discuss system performance, training of RF data, software used to deploy algorithms, and take a deep dive into one application.&lt;/span&gt;&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;&lt;span&gt;Applications of deep learning for systems and signals&lt;/span&gt;&lt;/li&gt;
&lt;li&gt;&lt;span&gt;How to leverage open source software for deployment&lt;/span&gt;&lt;/li&gt;
&lt;li&gt;Performance benchmarks of deep learning algorithms within a software defined radio system&lt;/li&gt;
&lt;/ul&gt;</description><dc:language>en-US</dc:language><generator>Telligent Community 12</generator></channel></rss>