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Discrete-Time Signal Processing - Massachusetts Institute of Technology

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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.

Informazioni importanti

Requisiti: 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.   


Dove e quando

Inizio Luogo


Jithin RJ
Il meglio One of the best courses ever educated in DSP. The mentor(s) push the points of confinement of learning through a blend of testing homework, classes and exams. On the off chance that your only earning source is DSP, then it is an unquestionable requirement take course - gainful for understudies and additionally experts. I could scarcely discover any imperfections in this course - the talk discussions are likewise of the most astounding quality.

Da migliorare Everything OK.

Corso realizzato: Ottobre 2016 | Recomendarías este centro? Sí.

Cosa impari in questo corso?

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.

Ulteriori informazioni

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).