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		<title>MIT OpenCourseWare: New Courses in Electrical Engineering and Computer Science</title>
		<description>New courses in Electrical Engineering and Computer Science from MIT OpenCourseWare, provider of free and open MIT course materials.</description>
		<link>http://ocw.mit.edu/courses/electrical-engineering-and-computer-science</link>
		<dc:date>2012-02-10T14:00:27+05:00</dc:date>
		<dc:publisher>MIT OpenCourseWare http://ocw.mit.edu</dc:publisher>
		<dc:language>en-US</dc:language>
		<dc:rights>Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm</dc:rights>
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		<title>6.241J Dynamic Systems and Control (MIT)</title>
		<description>The course addresses dynamic systems, i.e., systems that evolve with time. Typically these systems have inputs and outputs; it is of interest to understand how the input affects the output (or, vice-versa, what inputs should be given to generate a desired output). In particular, we will concentrate on systems that can be modeled by Ordinary Differential Equations (ODEs), and that satisfy certain linearity and time-invariance conditions. We will analyze the response of these systems to inputs and initial conditions. It is of particular interest to analyze systems obtained as interconnections (e.g., feedback) of two or more other systems. We will learn how to design (control) systems that ensure desirable properties (e.g., stability, performance) of the interconnection with a given dynamic system.&lt;br clear=&quot;both&quot; style=&quot;clear: both;&quot;/&gt;
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		<pheedo:origLink>http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-241j-dynamic-systems-and-control-spring-2011</pheedo:origLink>
		<dc:creator>Frazzoli, Emilio</dc:creator>
		<dc:creator>Dahleh, Munther</dc:creator>
		<dc:date>2011-12-28T16:31:42+05:00</dc:date>
		<dc:relation>6.241J</dc:relation>
		<dc:relation>16.338J</dc:relation>
		<dc:language>en-US</dc:language>
		<dc:subject>dynamic systems</dc:subject>
		<dc:subject>multiple inputs</dc:subject>
		<dc:subject>multiple outputs</dc:subject>
		<dc:subject>MIMO</dc:subject>
		<dc:subject>feedback</dc:subject>
		<dc:subject>control systems</dc:subject>
		<dc:subject>linear time-invariant</dc:subject>
		<dc:subject>optimal control</dc:subject>
		<dc:subject>robust control</dc:subject>
		<dc:subject>linear algebra</dc:subject>
		<dc:subject>least squares</dc:subject>
		<dc:publisher>MIT OpenCourseWare http://ocw.mit.edu</dc:publisher>
		<dc:rights>Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm</dc:rights>
	</item>
	<item rdf:about="http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-172-performance-engineering-of-software-systems-fall-2010">
		<title>6.172 Performance Engineering of Software Systems (MIT)</title>
		<description>Modern computing platforms provide unprecedented amounts of raw computational power. But significant complexity comes along with this power, to the point that making useful computations exploit even a fraction of the potential of the computing platform is a substantial challenge. Indeed, obtaining good performance requires a comprehensive understanding of all layers of the underlying platform, deep insight into the computation at hand, and the ingenuity and creativity required to obtain an effective mapping of the computation onto the machine. The reward for mastering these sophisticated and challenging topics is the ability to make computations that can process large amount of data orders of magnitude more quickly and efficiently and to obtain results that are unavailable with standard practice.
This class is a hands-on, project-based introduction to building scalable and high-performance software systems. Topics include performance analysis, algorithmic techniques for high performance, instruction-level optimizations, cache and memory hierarchy optimization, parallel programming, and building scalable distributed systems.
The course also includes design reviews with industry mentors, as described in this MIT News article.&lt;br clear=&quot;both&quot; style=&quot;clear: both;&quot;/&gt;
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		<pheedo:origLink>http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-172-performance-engineering-of-software-systems-fall-2010</pheedo:origLink>
		<dc:creator>Amarasinghe, Saman</dc:creator>
		<dc:creator>Leiserson, Charles</dc:creator>
		<dc:date>2011-12-22T16:54:49+05:00</dc:date>
		<dc:relation>6.172</dc:relation>
		<dc:language>en-US</dc:language>
		<dc:subject>performance analysis</dc:subject>
		<dc:subject>algorithmic techniques</dc:subject>
		<dc:subject>high performance</dc:subject>
		<dc:subject>instruction level optimization</dc:subject>
		<dc:subject>cache optimization</dc:subject>
		<dc:subject>memory optimization</dc:subject>
		<dc:subject>parallel programming</dc:subject>
		<dc:subject>scalable distributed systems</dc:subject>
		<dc:publisher>MIT OpenCourseWare http://ocw.mit.edu</dc:publisher>
		<dc:rights>Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm</dc:rights>
	</item>
	<item rdf:about="http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-262-discrete-stochastic-processes-spring-2011">
		<title>6.262 Discrete Stochastic Processes (MIT)</title>
		<description>Discrete stochastic processes are essentially probabilistic systems that evolve in time via random changes occurring at discrete fixed or random intervals. This course aims to help students acquire both the mathematical principles and the intuition necessary to create, analyze, and understand insightful models for a broad range of these processes.  The range of areas for which discrete stochastic-process models are useful is constantly expanding, and includes many applications in engineering, physics, biology, operations research and finance.&lt;br clear=&quot;both&quot; style=&quot;clear: both;&quot;/&gt;
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		<dc:creator>Gallager, Robert</dc:creator>
		<dc:date>2011-11-03T15:28:27+05:00</dc:date>
		<dc:relation>6.262</dc:relation>
		<dc:language>en-US</dc:language>
		<dc:subject>probability</dc:subject>
		<dc:subject>Poisson processes</dc:subject>
		<dc:subject>finite-state Markov chains</dc:subject>
		<dc:subject>renewal processes</dc:subject>
		<dc:subject>countable-state Markov chains</dc:subject>
		<dc:subject>Markov processes</dc:subject>
		<dc:subject>countable state spaces</dc:subject>
		<dc:subject>random walks</dc:subject>
		<dc:subject>large deviations</dc:subject>
		<dc:subject>martingales</dc:subject>
		<dc:publisher>MIT OpenCourseWare http://ocw.mit.edu</dc:publisher>
		<dc:rights>Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm</dc:rights>
	</item>
	<item rdf:about="http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-045j-automata-computability-and-complexity-spring-2011">
		<title>6.045J Automata, Computability, and Complexity (MIT)</title>
		<description>This course provides a challenging introduction to some of the central ideas of theoretical computer science. Beginning in antiquity, the course will progress through finite automata, circuits and decision trees, Turing machines and computability, efficient algorithms and reducibility, the P versus NP problem, NP-completeness, the power of randomness, cryptography and one-way functions, computational learning theory, and quantum computing. It examines the classes of problems that can and cannot be solved by various kinds of machines. It tries to explain the key differences between computational models that affect their power.&lt;br clear=&quot;both&quot; style=&quot;clear: both;&quot;/&gt;
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		<pheedo:origLink>http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-045j-automata-computability-and-complexity-spring-2011</pheedo:origLink>
		<dc:creator>Aaronson, Scott</dc:creator>
		<dc:date>2011-11-02T16:25:19+05:00</dc:date>
		<dc:relation>6.045J</dc:relation>
		<dc:relation>18.400J</dc:relation>
		<dc:language>en-US</dc:language>
		<dc:subject>finite automata</dc:subject>
		<dc:subject>Turing machine</dc:subject>
		<dc:subject>halting problem</dc:subject>
		<dc:subject>computability</dc:subject>
		<dc:subject>computational complexity</dc:subject>
		<dc:subject>polynomial time</dc:subject>
		<dc:subject>P</dc:subject>
		<dc:subject>NP</dc:subject>
		<dc:subject>NP complete</dc:subject>
		<dc:subject>probabilistic algorithms</dc:subject>
		<dc:subject>private-key cryptography</dc:subject>
		<dc:subject>public-key cryptography</dc:subject>
		<dc:subject>randomness</dc:subject>
		<dc:publisher>MIT OpenCourseWare http://ocw.mit.edu</dc:publisher>
		<dc:rights>Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm</dc:rights>
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	<item rdf:about="http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-061-introduction-to-electric-power-systems-spring-2011">
		<title>6.061 Introduction to Electric Power Systems (MIT)</title>
		<description>This course is an introductory subject in the field of electric power systems and electrical to mechanical energy conversion. Electric power has become increasingly important as a way of transmitting and transforming energy in industrial, military and transportation uses. Electric power systems are also at the heart of alternative energy systems, including wind and solar electric, geothermal and small scale hydroelectric generation.&lt;br clear=&quot;both&quot; style=&quot;clear: both;&quot;/&gt;
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		<link>http://www.pheedcontent.com/click.phdo?i=a37f1724392622adec6418bd55bf9482</link>
		<pheedo:origLink>http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-061-introduction-to-electric-power-systems-spring-2011</pheedo:origLink>
		<dc:creator>Kirtley, James</dc:creator>
		<dc:date>2011-09-30T12:20:12+05:00</dc:date>
		<dc:relation>6.061</dc:relation>
		<dc:relation>6.690</dc:relation>
		<dc:language>en-US</dc:language>
		<dc:subject>electric power systems</dc:subject>
		<dc:subject>energy conversion</dc:subject>
		<dc:subject>electrical energy</dc:subject>
		<dc:subject>mechanical energy</dc:subject>
		<dc:subject>electric transportation</dc:subject>
		<dc:subject>alternative energy</dc:subject>
		<dc:subject>electric circuits</dc:subject>
		<dc:subject>magnetic field devices</dc:subject>
		<dc:subject>lumped parameter electromechanics</dc:subject>
		<dc:publisher>MIT OpenCourseWare http://ocw.mit.edu</dc:publisher>
		<dc:rights>Content within individual OCW courses is (c) by the individual authors unless otherwise noted. MIT OpenCourseWare materials are licensed by the Massachusetts Institute of Technology under a Creative Commons License (Attribution-NonCommercial-ShareAlike). For further information see http://ocw.mit.edu/terms/index.htm</dc:rights>
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