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Tuesday, April 30, 2013

More Engineering Video Lectures

Hello everyone! This month I've various engineering video lectures from MIT and UNSW. They include aircraft systems engineering, digital signal processing, principles of digital communication and circuits and electronics.

Aircraft Systems Engineering (MIT, 22 lectures)

Course description:
16.885J offers a holistic view of the aircraft as a system, covering: basic systems engineering; cost and weight estimation; basic aircraft performance; safety and reliability; lifecycle topics; aircraft subsystems; risk analysis and management; and system realization. Small student teams retrospectively analyze an existing aircraft covering: key design drivers and decisions; aircraft attributes and subsystems; and operational experience. Oral and written versions of the case study are delivered. For the Fall 2005 term, the class focuses on a systems engineering analysis of the Space Shuttle. It offers study of both design and operations of the shuttle, with frequent lectures by outside experts. Students choose specific shuttle systems for detailed analysis and develop new subsystem designs using state of the art technology.

Course topics:
The Origins of the Space Shuttle. Space Shuttle History. Orbiter Sub-System Design. The Decision to Build the Shuttle. Orbiter Structure + Thermal Protection System. Propulsion - Space Shuttle Main Engines. Aerodynamics - (From Sub - to Hypersonic and Back). Landing and Mechanical Systems. OMS, RCS, Fuel Cells, Auxiliary Power Unit and Hydraulic Systems. The DoD and the Space Shuttle. Use of Subsystems as a Function of Flight Phase. Aerothermodynamics. Environmental Control Systems. Ground Operations - Launching the Shuttle. Space Shuttle Accidents. Guidance, Navigation and Control. Mission Control. Design Process as it Relates to the Shuttle. EVA and Robotics on the Shuttle. Systems Engineering for Space Shuttle Payloads. Test Flying the Space Shuttle.

Digital Signal Processing (University of New South Wales, 12 lectures)

Course description:
Signal Processing is the process of measuring, manipulating or analysing information. Signals of interest include biomedical data, audio, still or moving images, radar, and even DNA. Filtering techniques can be crucial in revealing and interpreting information present in a signal. ELEC3104 Digital Signal Processing is an introductory signal processing course which takes students through the steps necessary to design and implement filters for a range of signals.

Course topics:

Signals and Systems. Discrete-Time System. Introduction to Z-Transorm. Fourier Representation of Signal. Digital Signal Processing. Discrete-Time Fourier Transform. Analogue Filter Design. Digital Filter Design. Multirate Digital Signal Processing.

Principles of Digital Communications I (MIT, 24 lectures)

Course description:
The course serves as an introduction to the theory and practice behind many of today's communications systems. 6.450 forms the first of a two-course sequence on digital communication. The second class, 6.451, is offered in the spring. Topics covered include: digital communications at the block diagram level, data compression, Lempel-Ziv algorithm, scalar and vector quantization, sampling and aliasing, the Nyquist criterion, PAM and QAM modulation, signal constellations, finite-energy waveform spaces, detection, and modeling and system design for wireless communication.

Course topics:
Introduction. Discrete Source Encoding. Memory-less Sources. Entropy and Asymptotic Equipartition Property. Markov Sources. Quantization. High Rate Quantizers and Waveform Encoding. Measure. Discrete-Time Fourier Transforms. Degrees of Freedom. Signal Space. Nyquist Theory. Random Processes. Jointly Gaussian Random Vectors. Linear Functionals. Review; Introduction to Detection. Detection for Random Vectors and Processes. Theory of Irrelevance. Baseband Detection. Introduction of Wireless Communication. Doppler Spread. Discrete-Time Baseband Models for Wireless Channels. Detection for Flat Rayleigh Fading and Incoherent Channels. Case Study on Code Division Multiple Access.

Principles of Digital Communications II (MIT, 25 lectures)

Course description:
This course is the second of a two-term sequence with 6.450. The focus is on coding techniques for approaching the Shannon limit of additive white Gaussian noise (AWGN) channels, their performance analysis, and design principles. After a review of 6.450 and the Shannon limit for AWGN channels, the course begins by discussing small signal constellations, performance analysis and coding gain, and hard-decision and soft-decision decoding. It continues with binary linear block codes, Reed-Muller codes, finite fields, Reed-Solomon and BCH codes, binary linear convolutional codes, and the Viterbi algorithm. More advanced topics include trellis representations of binary linear block codes and trellis-based decoding; codes on graphs; the sum-product and min-sum algorithms; the BCJR algorithm; turbo codes, LDPC codes and RA codes; and performance of LDPC codes with iterative decoding. Finally, the course addresses coding for the bandwidth-limited regime, including lattice codes, trellis-coded modulation, multilevel coding and shaping. If time permits, it covers equalization of linear Gaussian channels.

Course topics:
Introduction Sampling Theorem. Performance of Small Signal Constellations. Hard-decision and Soft-decision Decoding. Hard-decision and Soft-decision Decoding. Introduction to Binary Block Codes. Introduction to Binary Block Codes. Introduction to Binary Block Codes. Introduction to Finite Fields. Reed-Solomon Codes. Introduction to Convolutional Codes. Trellis Representations of Binary Linear Block Codes. Codes on Graphs. The Sum-Product Algorithm. Turbo, LDPC, and RA Codes. Lattice and Trellis Codes. Lattice and Trellis Codes. Linear Gaussian Channels.

Circuits and Electronics (MIT, 25 lectures)

Course description:
6.002 is designed to serve as a first course in an undergraduate electrical engineering (EE), or electrical engineering and computer science (EECS) curriculum. At MIT, 6.002 is in the core of department subjects required for all undergraduates in EECS. The course introduces the fundamentals of the lumped circuit abstraction. Topics covered include: resistive elements and networks; independent and dependent sources; switches and MOS transistors; digital abstraction; amplifiers; energy storage elements; dynamics of first- and second-order networks; design in the time and frequency domains; and analog and digital circuits and applications. Design and lab exercises are also significant components of the course. 6.002 is worth 4 Engineering Design Points. The 6.002 content was created collaboratively by Profs. Anant Agarwal and Jeffrey H. Lang.

Course topics:
Introduction and Lumped Abstraction. Basic Circuit Analysis Method. Superposition, Thévenin and Norton. The Digital Abstraction. Inside the Digital Gate. Nonlinear Analysis. Incremental Analysis. Dependent Sources and Amplifiers. Mosfet Amplifier Large Signal Analysis. Amplifiers - Small Signal Model. Small Signal Circuits. Capacitors and First-Order Systems. Digital Circuit Speed. State and Memory. Second-Order Systems. Sinusoidal Steady State. The Impedance Model. Filters. The Operational Amplifier Abstraction. Operational Amplifier Circuits. Op Amps Positive Feedback. Energy and Power. Energy, CMOS. Violating the Abstraction Barrier.

Enjoy the videos!

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