Discrete-Time Signal Processing

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edX online courses
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Harvard University, the Massachusetts Institute of Technology, and the University of California, Berkeley, are just some of the schools that you have at your fingertips with edX. Through massive open online courses (MOOCs) from the world's best universities, you can develop your knowledge in literature, math, history, food and nutrition, and more. These online classes are taught by highly-regarded experts in the field. If you take a class on computer science through Harvard, you may be taught by David J. Malan, a senior lecturer on computer science at Harvard University for the School of Engineering and Applied Sciences. But there's not just one professor - you have access to the entire teaching staff, allowing you to receive feedback on assignments straight from the experts. Pursue a Verified Certificate to document your achievements and use your coursework for job and school applications, promotions, and more. EdX also works with top universities to conduct research, allowing them to learn more about learning. Using their findings, edX is able to provide students with the best and most effective courses, constantly enhancing the student experience.

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Course Description

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 be...

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). 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.

6.341x and this freely-available version were developed through the support and encouragement of the MIT Department of Electrical Engineering and Computer Science, the MIT Office of Digital Learning, and the MIT Research Laboratory of Electronics.

This course can be cited as: Alan V. Oppenheim and Thomas A. Baran, 6.341x Discrete-Time Signal Processing, on edX, Summer 2016. https://www.edx.org/course/discrete-time-signal-processing-mitx-6-341x-1

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Jithin RJ profile image
Jithin RJ profile image

Jithin RJ

10/10 starsCompleted
2 years, 9 months ago
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.
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