Discrete Time Signals and Systems, Part 1: Time Domain  Rice University
edX
Online
3 Meinungen

The course was lot of fun. I found it was relative easy to do, even without having any experience of the topic. Hearing only part 1 alone does not make sense, the two parts belong together.
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Discrete Time Signals and Systems, Part 1: Time Domain is a 4week introduction to discrete time signals offered by Rice University through the edX platform. This course was originally 8 weeks, but edX split it up into two parts, one covering the time domain and one addressing the frequency domain. Major course topics include signal properties, signals as vectors, linear timeinvariant systems and convolution. The course requires some linear algebra and calculus (it has a precourse assessment) as well as some basic programming in MATLAB. You don't need to know any MATLAB going in, but if you do you can skip the tutorial. Grading is based on a combination of comprehension questions, homework quizzes, peer graded free responses and a final exam. All of the course content other than assignments is available immediately so you can work ahead if you want to. Discrete Time Signals and Systems started around the same time as a similar signal processing course on Coursera called "Digital Signal Processing." I found Discrete Time Signals to be much more approachable than the Coursera course; it introduces concepts at a steady but manageable pace and doesn't overload you with math right out of the gate. The course isn't easy, but it isn't too difficult. The lecture videos are welldone and the instruction is very good, although some videos could stand to be broken up into multiple parts. Professor Baraniuk tends to stutter, but it didn't really bother me or detract from the quality of the instruction. The MATLAB programming questions are baked right into the edX website and let you get some handson experience with the concepts. The final exam is "closed book" which I think is a mistake as it promotes guessing over learning. All in all, Discrete Time Signals and Systems Part 1 is an excellent introduction to signal processing that is likely to be more accessible than other courses on the same subject you may find elsewhere. The stage is set for a deeper dive into signal processing in Part 2.
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DSP is beautiful. The more you learn, the more you fall in love with it. If you wanna learn DSP in an interesting way, this is the best place and you've got the best professor here. This course is a bit challenging course; needs lot of hand work. I did this course in the first offering and i'm so grateful to my professor, Richard. Thanks :)
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Kostenlos
Wichtige informationen
 Kurs
 Online
 Wann:
Freie Auswahl
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.
Voraussetzungen: Advanced calculus, complex algebra, and linear algebra.
Veranstaltungsort(e)Wo und wann
Beginn  Lage 

Freie Auswahl 
Online

Meinungen
E
Exstudent
12.11.2016
Das Beste
The course was lot of fun. I found it was relative easy to do, even without having any experience of the topic. Hearing only part 1 alone does not make sense, the two parts belong together.
Zu verbessern Nothing.
Kurs abgeschlossen: November 2016  Recomendarías este centro? Sí.
Zu verbessern Nothing.
Kurs abgeschlossen: November 2016  Recomendarías este centro? Sí.
G
Greg Hamel
05.09.2016
Das Beste
Discrete Time Signals and Systems, Part 1: Time Domain is a 4week introduction to discrete time signals offered by Rice University through the edX platform. This course was originally 8 weeks, but edX split it up into two parts, one covering the time domain and one addressing the frequency domain. Major course topics include signal properties, signals as vectors, linear timeinvariant systems and convolution. The course requires some linear algebra and calculus (it has a precourse assessment) as well as some basic programming in MATLAB. You don't need to know any MATLAB going in, but if you do you can skip the tutorial. Grading is based on a combination of comprehension questions, homework quizzes, peer graded free responses and a final exam. All of the course content other than assignments is available immediately so you can work ahead if you want to. Discrete Time Signals and Systems started around the same time as a similar signal processing course on Coursera called "Digital Signal Processing." I found Discrete Time Signals to be much more approachable than the Coursera course; it introduces concepts at a steady but manageable pace and doesn't overload you with math right out of the gate. The course isn't easy, but it isn't too difficult. The lecture videos are welldone and the instruction is very good, although some videos could stand to be broken up into multiple parts. Professor Baraniuk tends to stutter, but it didn't really bother me or detract from the quality of the instruction. The MATLAB programming questions are baked right into the edX website and let you get some handson experience with the concepts. The final exam is "closed book" which I think is a mistake as it promotes guessing over learning. All in all, Discrete Time Signals and Systems Part 1 is an excellent introduction to signal processing that is likely to be more accessible than other courses on the same subject you may find elsewhere. The stage is set for a deeper dive into signal processing in Part 2.
Zu verbessern Everything was positive.
Kurs abgeschlossen: September 2016  Recomendarías este centro? Sí.
Zu verbessern Everything was positive.
Kurs abgeschlossen: September 2016  Recomendarías este centro? Sí.
E
Exstudent
15.03.2016
Das Beste
DSP is beautiful. The more you learn, the more you fall in love with it. If you wanna learn DSP in an interesting way, this is the best place and you've got the best professor here. This course is a bit challenging course; needs lot of hand work. I did this course in the first offering and i'm so grateful to my professor, Richard. Thanks :)
Zu verbessern Nothing.
Kurs abgeschlossen: März 2016  Recomendarías este centro? Sí.
Zu verbessern Nothing.
Kurs abgeschlossen: März 2016  Recomendarías este centro? Sí.
Was lernen Sie in diesem Kurs?
IT  systems 
Themenkreis
Technological innovations have revolutionized the way we view and interact with the world around us. Editing a photo, remixing a song, automatically measuring and adjusting chemical concentrations in a tank: each of these tasks requires realworld 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 discretetime signals and systems in both the time and frequency domains. Students will learn convolution, discrete Fourier transforms, the ztransform, 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 (onedimensional 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
What you'll learn
 Types of Fundamental Signals
 Vector Description of Signals
 Introduction to Discrete Time Systems
 Convolution
Zusätzliche Informationen
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 WisconsinMadison, and the University of Illinois at UrbanaChampaign. 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).