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Discrete Time Signals and Systems, Part 1: Time Domain - Rice University

3 opinions


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Enter the world of signal processing: analyze and extract meaning from the signals around us!
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.

Important information

Requirements: Advanced calculus, complex algebra, and linear algebra.


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What I would highlight The course was great fun. I discovered it was relatively simple to do, even without having any involvement of the subject. Listening to just section 1 alone does not bode well, the two sections have a place together.

What could be improved Nothing.

Course taken: August 2016 | Recomendarías este centro? Sí.

What I would highlight I observed Discrete Time Signals to be a great deal more congenial than the Coursera course; it presents ideas at an enduring however sensible pace and does not over-burden you with math ideal out of the door. The course is not simple, yet it is not excessively troublesome. The address recordings are well-done and the guideline is great, albeit a few recordings could remain to be separated into different parts. Teacher Baraniuk tends to stammer, however it didn't generally trouble me or bring down the nature of the direction. The MATLAB programming inquiries are prepared directly into the edX site and let you get a few hands-on involvement with the ideas. The last test of the year is "shut book" which I believe is a misstep as it advances speculating over learning. With everything taken into account, Discrete Time Signals and Systems Part 1 is a magnificent prologue to flag preparing that is probably going to be more open than different courses on a similar subject you may discover somewhere else. The stage is set for a more profound plunge into flag handling in Part 2.

What could be improved Everything was positive.

Course taken: October 2016 | Recomendarías este centro? Sí.

What I would highlight DSP is lovely. The more you take in, the more you begin to look all starry eyed at it. On the off chance that you wanna learn DSP in a fascinating way, this is the best place and you have the best educator here. This course is somewhat testing course; requires good amount of pragmatic work. I did this course in the principal offering and I am so thankful to my teacher, Richard. Much appreciated :)

What could be improved Nothing.

Course taken: December 2016 | Recomendarías este centro? Sí.

What you'll learn on the course


Course programme

Technological innovations have revolutionized the way we view and interact with the world around us. Editing a photo, re-mixing a song, automatically measuring and adjusting chemical concentrations in a tank: each of these tasks requires real-world data to be captured by a computer and then manipulated digitally to extract the salient information. Ever wonder how signals from the physical world are sampled, stored, and processed without losing the information required to make predictions and extract meaning from the data? Students will find out in this rigorous mathematical introduction to the engineering field of signal processing: the study of signals and systems that extract information from the world around us. This course will teach students to analyze discrete-time signals and systems in both the time and frequency domains. Students will learn convolution, discrete Fourier transforms, the z-transform, and digital filtering. Students will apply these concepts in interactive MATLAB programming exercises (all done in browser, no download required). Part 1 of this course analyzes signals and systems in the time domain. Part 2 covers frequency domain analysis. Prerequisites include strong problem solving skills, the ability to understand mathematical representations of physical systems, and advanced mathematical background (one-dimensional integration, matrices, vectors, basic linear algebra, imaginary numbers, and sum and series notation). Part 1 is a prerequisite for Part 2. This course is an excerpt from an advanced undergraduate class at Rice University taught to all electrical and computer engineering majors.

What you'll learn
  • Types of Fundamental Signals
  • Vector Description of Signals 
  • Introduction to Discrete Time Systems
  • Convolution

Additional information

Richard G. Baraniuk Professor Richard G. Baraniuk grew up in Winnipeg, Canada, the coldest city in the world with a population over 600,000. He studied Electrical Engineering at the University of Manitoba, the University of Wisconsin-Madison, and the University of Illinois at Urbana-Champaign. Dr. Baraniuk joined Rice University in Houston, Texas, in 1993 and is now the Victor E. Cameron Professor of Electrical and Computer Engineering. He is a member of the Digital Signal Processing (DSP) group and Director of the Rice center for Digital Learning and Scholarship (RDLS).