<?xml version="1.0" encoding="UTF-8"?><rss version="2.0"
	xmlns:content="http://purl.org/rss/1.0/modules/content/"
	xmlns:wfw="http://wellformedweb.org/CommentAPI/"
	xmlns:dc="http://purl.org/dc/elements/1.1/"
	xmlns:atom="http://www.w3.org/2005/Atom"
	xmlns:sy="http://purl.org/rss/1.0/modules/syndication/"
	xmlns:slash="http://purl.org/rss/1.0/modules/slash/"
	>

<channel>
	<title>Computer Archives &#8212; MATLAB Number ONE</title>
	<atom:link href="https://matlab1.com/category/computer/feed/" rel="self" type="application/rss+xml" />
	<link>https://matlab1.com/category/computer/</link>
	<description>MATLAB Simulink &#124; Tutorial &#124; Code &#124; Project</description>
	<lastBuildDate>Sun, 07 Oct 2018 19:17:39 +0000</lastBuildDate>
	<language>en-GB</language>
	<sy:updatePeriod>
	hourly	</sy:updatePeriod>
	<sy:updateFrequency>
	1	</sy:updateFrequency>
	

<image>
	<url>https://matlab1.com/wp-content/uploads/2018/08/icon1-100x100.png</url>
	<title>Computer Archives &#8212; MATLAB Number ONE</title>
	<link>https://matlab1.com/category/computer/</link>
	<width>32</width>
	<height>32</height>
</image> 
	<item>
		<title>Python projektet</title>
		<link>https://matlab1.com/python-projektet/</link>
					<comments>https://matlab1.com/python-projektet/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Sat, 16 Jun 2018 04:38:59 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[Deep Learning]]></category>
		<category><![CDATA[image processing]]></category>
		<category><![CDATA[2D och 3D-funktionalitetsverktyg]]></category>
		<category><![CDATA[Ansiktsigenkänningssystem]]></category>
		<category><![CDATA[Artificiellt nervsystem]]></category>
		<category><![CDATA[Besluts träning]]></category>
		<category><![CDATA[bildbehandling]]></category>
		<category><![CDATA[Boosting]]></category>
		<category><![CDATA[dataflödesprogrammering]]></category>
		<category><![CDATA[dataprofilering och analys]]></category>
		<category><![CDATA[datorsyn]]></category>
		<category><![CDATA[Datorsyn och mönsterigenkänning]]></category>
		<category><![CDATA[djupa neurala nätverk]]></category>
		<category><![CDATA[Djupa neurala nätverk (DNN)]]></category>
		<category><![CDATA[djupt lärande neurala nätverk]]></category>
		<category><![CDATA[Egomotionsuppskattning]]></category>
		<category><![CDATA[Förstärkande lärande]]></category>
		<category><![CDATA[Förväntnings-maximeringsalgoritm]]></category>
		<category><![CDATA[Gensigenkänning]]></category>
		<category><![CDATA[gradient boosting]]></category>
		<category><![CDATA[Gradient öka träd]]></category>
		<category><![CDATA[Introduktion till maskinlärning med Python]]></category>
		<category><![CDATA[k-means]]></category>
		<category><![CDATA[k-närmaste grannalgoritm]]></category>
		<category><![CDATA[klassificering]]></category>
		<category><![CDATA[klustringsalgoritmer]]></category>
		<category><![CDATA[Konstgjord intelligens]]></category>
		<category><![CDATA[manipulera numeriska tabeller och tidsserier]]></category>
		<category><![CDATA[Mänsklig dator interaktion (HCI)]]></category>
		<category><![CDATA[Maskininlärningsbibliotek för Python]]></category>
		<category><![CDATA[Mobil robotik]]></category>
		<category><![CDATA[Motion tracking]]></category>
		<category><![CDATA[Naive Bayes klassificerare]]></category>
		<category><![CDATA[neuralt nätverk]]></category>
		<category><![CDATA[neuralt nätverk i Python]]></category>
		<category><![CDATA[numerisk matematik]]></category>
		<category><![CDATA[Objektidentifiering]]></category>
		<category><![CDATA[Ökad verklighet]]></category>
		<category><![CDATA[oövervakat lärande]]></category>
		<category><![CDATA[Python för dataanalys]]></category>
		<category><![CDATA[Python projekt hjälp]]></category>
		<category><![CDATA[Rörelseförståelse]]></category>
		<category><![CDATA[Segmentering och erkännande]]></category>
		<category><![CDATA[Slumpmässig skog]]></category>
		<category><![CDATA[slumpmässiga skogar]]></category>
		<category><![CDATA[Stereopsis stereosyn: djupuppfattning från 2 kameror]]></category>
		<category><![CDATA[stöd vektor maskiner]]></category>
		<category><![CDATA[Struktur från rörelse (SFM)]]></category>
		<category><![CDATA[Support vektor maskin (SVM)]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=5631</guid>

					<description><![CDATA[<p>Jag är en pythonprogrammerare. Jag har fyra års erfarenhet av python. Jag är redo att acceptera Python-projektet. &#160; Keras, TensorFlow, Scipy, Numpy, Konstgjort neuralt nätverk i Python, Bildbehandling i Python, OpenCV, Pybrain, Matplotlib, Scikit-Learn , Pandas Djupt lärande i Python, Maskinlärning i Python Kontakt: matlab120 [[attt]] gmail [[[dot]] com Vänligen skicka e-post på engelska. &#160; [&#8230;]</p>
<p>The post <a href="https://matlab1.com/python-projektet/">Python projektet</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
					<wfw:commentRss>https://matlab1.com/python-projektet/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Data science interview preparation checklist:</title>
		<link>https://matlab1.com/data-science-interview-preparation-checklist/</link>
					<comments>https://matlab1.com/data-science-interview-preparation-checklist/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Tue, 12 Jun 2018 12:11:52 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[data mining]]></category>
		<category><![CDATA[Deep Learning]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=5600</guid>

					<description><![CDATA[<p>1. Study the company 2. Understand how the company makes money 3. Dress slightly above how you expect the company dresses 4. Practice interviewing (have someone else quiz you) and be able to answer why you would be a good fit at that company 5. Have questions ready for the interviewer 6. Practice a 2-minute description [&#8230;]</p>
<p>The post <a href="https://matlab1.com/data-science-interview-preparation-checklist/">Data science interview preparation checklist:</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
					<wfw:commentRss>https://matlab1.com/data-science-interview-preparation-checklist/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Sinc interpolation on input waveforms</title>
		<link>https://matlab1.com/sinc-interpolation-on-input-waveforms/</link>
					<comments>https://matlab1.com/sinc-interpolation-on-input-waveforms/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Thu, 15 Mar 2018 13:28:46 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[image processing]]></category>
		<category><![CDATA[MATLAB]]></category>
		<category><![CDATA[MATLAB code]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=4378</guid>

					<description><![CDATA[<p>function [yi, ypi] = sincdint(x, y, xi, c) % SINCDINT 1-D piecewise discrete sinc interpolation % SINCDINT(X,Y,XI,C) interpolates to find YI, the values of the % underlying function Y at the points in the array XI, using % piecewise discrete sinc interpolation. X and Y must be vectors % of length N. % % C [&#8230;]</p>
<p>The post <a href="https://matlab1.com/sinc-interpolation-on-input-waveforms/">Sinc interpolation on input waveforms</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
					<wfw:commentRss>https://matlab1.com/sinc-interpolation-on-input-waveforms/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Fire-i and NAVITAR Scope Setup</title>
		<link>https://matlab1.com/fire-i-and-navitar-scope-setup/</link>
					<comments>https://matlab1.com/fire-i-and-navitar-scope-setup/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Thu, 15 Mar 2018 13:15:34 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[image processing]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=4370</guid>

					<description><![CDATA[<p>This section details the use of the Fire-i program to control the NAVITAR scope for capturing images and movies to use with the line tracking program or for imaging purposes. 1. Connect the Firewire cable to the NAVITAR scope. 2. Open Fire-i . 3. Ensure the settings are as shown in Figure 1. 4. Click Start [&#8230;]</p>
<p>The post <a href="https://matlab1.com/fire-i-and-navitar-scope-setup/">Fire-i and NAVITAR Scope Setup</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
					<wfw:commentRss>https://matlab1.com/fire-i-and-navitar-scope-setup/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Paper</title>
		<link>https://matlab1.com/paper/</link>
					<comments>https://matlab1.com/paper/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Wed, 07 Mar 2018 19:14:26 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=6381</guid>

					<description><![CDATA[<p>https://scholar.google.com/citations?user=1zIFSngAAAAJ&#38;hl=en &#160; https://matlab1.com/wp-content/uploads/papers/Analog CMOS Implementation of order weight Average operator for fuzzy logic controller chip.pdf &#160; https://matlab1.com/wp-content/uploads/papers/High speed ant colony optimization CMOS chip.pdf . https://matlab1.com/wp-content/uploads/papers/Implementation of centroid defuzzifier block using CMOS circuits.pdf . https://matlab1.com/wp-content/uploads/papers/Implementation of CMOS flexible fuzzy logic controller chip in current mode.pdf . https://matlab1.com/wp-content/uploads/papers/Low noise CMOS implementation of order weight average operator for [&#8230;]</p>
<p>The post <a href="https://matlab1.com/paper/">Paper</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
					<wfw:commentRss>https://matlab1.com/paper/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Amplify And Forward Full Duplex Relay OFDM Transmission Scheme</title>
		<link>https://matlab1.com/amplify-forward-full-duplex-relay-ofdm-transmission-scheme/</link>
					<comments>https://matlab1.com/amplify-forward-full-duplex-relay-ofdm-transmission-scheme/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Mon, 04 Dec 2017 17:23:30 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[decode and forward]]></category>
		<category><![CDATA[OFDM]]></category>
		<category><![CDATA[self-interference]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=4040</guid>

					<description><![CDATA[<p>Amplify And Forward Full Duplex Relay OFDM Transmission Scheme Recently, relay-assisted wireless communication system has been undergoing extensive development in both industry and academia. By receiving, processing, and retransmitting radio signals, relay networks oer an energy efficient and low cost solution to expand coverage of wireless connections. The two most typical relaying protocols are AF [&#8230;]</p>
<p>The post <a href="https://matlab1.com/amplify-forward-full-duplex-relay-ofdm-transmission-scheme/">Amplify And Forward Full Duplex Relay OFDM Transmission Scheme</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
					<wfw:commentRss>https://matlab1.com/amplify-forward-full-duplex-relay-ofdm-transmission-scheme/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Robust Precoding For MIMO OFDM With Insufficient CP</title>
		<link>https://matlab1.com/robust-precoding-mimo-ofdm-insufficient-cp/</link>
					<comments>https://matlab1.com/robust-precoding-mimo-ofdm-insufficient-cp/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Mon, 04 Dec 2017 17:16:36 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[10257226]]></category>
		<category><![CDATA[CP]]></category>
		<category><![CDATA[MIMO]]></category>
		<category><![CDATA[OFDM]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=4038</guid>

					<description><![CDATA[<p>Robust Precoding For MIMO OFDM With Insufficient CP MIMO channels arising from the use of multiple antennas at both transmitter and receiver have received continuously attention because they provide an signicant increase in capacity over the single input single output (SISO) counterpart. Alternatively, techniques can also be applied to MIMO for enhancement of the link robustness. [&#8230;]</p>
<p>The post <a href="https://matlab1.com/robust-precoding-mimo-ofdm-insufficient-cp/">Robust Precoding For MIMO OFDM With Insufficient CP</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
					<wfw:commentRss>https://matlab1.com/robust-precoding-mimo-ofdm-insufficient-cp/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Channel Independent Precoding Design For MIMO OFDM With Insufficient CP</title>
		<link>https://matlab1.com/channel-independent-precoding-design-mimo-ofdm-insufficient-cp/</link>
					<comments>https://matlab1.com/channel-independent-precoding-design-mimo-ofdm-insufficient-cp/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Mon, 04 Dec 2017 17:13:39 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[10257226]]></category>
		<category><![CDATA[CP]]></category>
		<category><![CDATA[MIMO]]></category>
		<category><![CDATA[OFDM]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=4036</guid>

					<description><![CDATA[<p>Channel Independent Precoding Design For MIMO OFDM With Insufficient CP In OFDM system, the frequency domain channel is divided into a set of parallel narrow subchannels, therefore eliminating or reducing the innate intersymbol interference (ISI) in the wideband channel. OFDM systems transform from the ISI channel to the ISI free subchannels by resorting to IDFT and [&#8230;]</p>
<p>The post <a href="https://matlab1.com/channel-independent-precoding-design-mimo-ofdm-insufficient-cp/">Channel Independent Precoding Design For MIMO OFDM With Insufficient CP</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
					<wfw:commentRss>https://matlab1.com/channel-independent-precoding-design-mimo-ofdm-insufficient-cp/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Power Electronics Interface Topologies</title>
		<link>https://matlab1.com/power-electronics-interface-topologies/</link>
					<comments>https://matlab1.com/power-electronics-interface-topologies/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Thu, 30 Nov 2017 22:53:25 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[10255848]]></category>
		<category><![CDATA[Current Source Converters]]></category>
		<category><![CDATA[NPC]]></category>
		<category><![CDATA[Power Electronics Interface Topologies]]></category>
		<category><![CDATA[wind turbine]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=4004</guid>

					<description><![CDATA[<p>Power Electronics Interface Topologies The incorporation of solid-state power converters in wind energy conversion systems has increased over the past decade in order to improve control of the wind turbine and to improve its interconnection issues with the grid . These power converters are also used to control the active and reactive power injected into [&#8230;]</p>
<p>The post <a href="https://matlab1.com/power-electronics-interface-topologies/">Power Electronics Interface Topologies</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
					<wfw:commentRss>https://matlab1.com/power-electronics-interface-topologies/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
		<item>
		<title>Wind Turbine Topologies</title>
		<link>https://matlab1.com/wind-turbine-topologies/</link>
					<comments>https://matlab1.com/wind-turbine-topologies/#respond</comments>
		
		<dc:creator><![CDATA[global MATLAB]]></dc:creator>
		<pubDate>Thu, 30 Nov 2017 16:23:37 +0000</pubDate>
				<category><![CDATA[Computer]]></category>
		<category><![CDATA[10255848]]></category>
		<category><![CDATA[Voltage Source Converters]]></category>
		<category><![CDATA[Wind Turbine Topologies]]></category>
		<category><![CDATA[Wound Rotor Induction Generator]]></category>
		<guid isPermaLink="false">https://matlab1.com/?p=3998</guid>

					<description><![CDATA[<p>Wind Turbine Topologies The variable speed wind turbines are commonly categorized into Indirect Drive Wind Turbines (IDWTs) and DDWTs. In IDWTs, the low-speed shaft is connected to the high-speed shaft through a gearbox, whereas DDWTs have a low-speed shaft that is directly connected to the generator . The two most commonly used topologies for wind [&#8230;]</p>
<p>The post <a href="https://matlab1.com/wind-turbine-topologies/">Wind Turbine Topologies</a> appeared first on <a href="https://matlab1.com">MATLAB Number ONE</a>.</p>
]]></description>
		
					<wfw:commentRss>https://matlab1.com/wind-turbine-topologies/feed/</wfw:commentRss>
			<slash:comments>0</slash:comments>
		
		
			</item>
	</channel>
</rss>
