http://hdl.handle.net/1721.1/33986 Electrical Engineering and Computer Science (6) Thu, 20 Jun 2013 07:21:01 GMT 2013-06-20T07:21:01Z http://hdl.handle.net/1721.1/78251 6.003 Signals and Systems, Spring 2010 Freeman, Dennis 6.003 covers the fundamentals of signal and system analysis, focusing on representations of discrete-time and continuous-time signals (singularity functions, complex exponentials and geometrics, Fourier representations, Laplace and Z transforms, sampling) and representations of linear, time-invariant systems (difference and differential equations, block diagrams, system functions, poles and zeros, convolution, impulse and step responses, frequency responses). Applications are drawn broadly from engineering and physics, including feedback and control, communications, and signal processing. Tue, 01 Jun 2010 00:00:00 GMT http://hdl.handle.net/1721.1/78251 2010-06-01T00:00:00Z http://hdl.handle.net/1721.1/77902 18.337J / 6.338J Applied Parallel Computing (SMA 5505), Spring 2005 Edelman, Alan Applied Parallel Computing is an advanced interdisciplinary introduction to applied parallel computing on modern supercomputers. Wed, 01 Jun 2005 00:00:00 GMT http://hdl.handle.net/1721.1/77902 2005-06-01T00:00:00Z http://hdl.handle.net/1721.1/76254 6.253 Convex Analysis and Optimization, Spring 2010 Bertsekas, Dimitri This course will focus on fundamental subjects in (deterministic) optimization, connected through the themes of convexity, geometric multipliers, and duality. The aim is to develop the core analytical and computational issues of continuous optimization, duality, and saddle point theory using a handful of unifying principles that can be easily visualized and readily understood. The mathematical theory of convex sets and functions will be central, and will allow an intuitive, highly visual, geometrical approach to the subject. This theory will be developed in detail and in parallel with the optimization topics. The first part of the course develops the analytical issues of convexity and duality. The second part is devoted to convex optimization algorithms, and their applications to a variety of large-scale optimization problems from resource allocation, machine learning, engineering design, and other areas. Tue, 01 Jun 2010 00:00:00 GMT http://hdl.handle.net/1721.1/76254 2010-06-01T00:00:00Z http://hdl.handle.net/1721.1/75824 6.005 Elements of Software Construction, Fall 2008 Jackson, Daniel; Miller, Robert This course provides an introduction to the fundamental principles and techniques of software development that have greatest impact on practice. Topics include capturing the essence of a problem by recognizing and inventing suitable abstractions; key paradigms, including state machines, functional programming, and object-oriented programming; use of design patterns to bridge gap between models and code; the role of interfaces and specification in achieving modularity and decoupling; reasoning about code using invariants; testing, test-case generation and coverage; and essentials of programming with objects, functions, and abstract types. The course includes exercises in modeling, design, implementation and reasoning. Mon, 01 Dec 2008 00:00:00 GMT http://hdl.handle.net/1721.1/75824 2008-12-01T00:00:00Z