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Discrete-Time Signal Processing - Massachusetts Institute of Technology

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Wichtige informationen

  • Kurs
  • Online
  • Wann:
    Freie Auswahl

A focused view into the theory behind modern discrete-time signal processing systems and applications.With this course you earn while you learn, you gain recognized qualifications, job specific skills and knowledge and this helps you stand out in the job market.

Wichtige informationen

Voraussetzungen: 6.341x assumes a strong background in the basics of signals and systems and some more advanced exposure to that basic material through an advanced undergraduate subject and/or industrial or research experience.   


Wo und wann

Beginn Lage
Freie Auswahl



Das Beste One of the best courses ever taught in DSP. The instructor(s) push the limits of learning through a mix of challenging homework, lectures and exams. If your bread and butter is DSP, then it is a must-take course - beneficial for students as well as professionals. I could hardly find any flaws in this course - the discussion forums are also of the highest quality.

Zu verbessern Everything OK.

Kurs abgeschlossen: April 2015 | Recomendarías este centro? Sí.

Was lernen Sie in diesem Kurs?

Signal processing
Computer Science
TSignal Processing
Processing Systems


6.341x is designed to provide both an in-depth and an intuitive understanding of the theory behind modern discrete-time signal processing systems and applications.  The course begins with a review and extension of the basics of signal processing including a discussion of group delay and minimum-phase systems, and the use of discrete-time (DT) systems for processing of continuous-time (CT) signals.  The course develops flow-graph and block diagram structures including lattice filters for implementing DT systems, and techniques for the design of DT filters. Parametric signal modeling and the efficient implementation of DT multirate and sampling rate conversion systems are discussed and developed. An in-depth development of the DFT and its computation as well as its use for spectral analysis and for filtering is presented. This component of the course includes a careful and insightful development of the relationship between the time-dependent Fourier transform and the use of filter banks for both spectral analysis and signal coding.

6.341x is organized around eleven units each typically consisting of a set of two to four topics. The source material for learning each topic includes suggested reading in the course text, clarifying notes, other related reading, and video excerpts and will include an interactive on-line discussion forum. The course text is the widely used text by Oppenheim and Schafer (third edition), available on the course website in viewable format. The video segments are adapted from live video recordings of the MIT residential course. 

Each topic includes a set of automatically-graded exercises for self-assessment and to help in digesting and understanding the basics of the topic, and in some cases to preview topics. A typical unit in the course concludes with a set of more extensive problems to help in integrating the topics and developing a deeper understanding. Automatic grading of your answers to these problems as well as solutions will be provided.

Zusätzliche Informationen

Alan V. Oppenheim Prof. Oppenheim is Professor of Electrical Engineering and Computer Science and a MacVicar Faculty Fellow at the Massachusetts Institute of Technology (MIT). He received the S.B. and S.M. degrees in 1961 and the Sc.D. degree in 1964, all in electrical engineering, from the Massachusetts Institute of Technology. He leads the Digital Signal Processing Research Group (DSPG) in the MIT Research Laboratory of Electronics (RLE).