Digital Signal Processing is the branch of engineering that, in the space of just a few decades, has enabled unprecedented levels of interpersonal communication and of on-demand entertainment. By reworking the principles of electronics, telecommunication and computer science into a unifying paradigm, DSP is a the heart of the digital revolution that brought us CDs, DVDs, MP3 players, mobile phones and countless other devices.
Este curso faz parte do Programa de cursos integrados Processamento Digital de Sinais
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Informações sobre o curso
O que você vai aprender
The difference between continuous and discrete time
Sampling and interpolation
Quantization, A/D and D/A converters
Multirate signal processing
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Programa - O que você aprenderá com este curso
Module 3.1: Interpolation and Sampling
From continuous time to discrete time and vice versa.
Module 3.2: Aliasing
What happens when we sample continuous-time signals and problems we should anticipate.
Module 3.3: Multirate Signal Processing
How to change the sampling rate entirely from the discrete-time domain.
Module 3:4: A/D and D/A Conversion
Going from analog to digital, and vice-versa.
Avaliações
- 5 stars92,18%
- 4 stars4,68%
- 1 star3,12%
Principais avaliações do DIGITAL SIGNAL PROCESSING 3: ANALOG VS DIGITAL
Excellent continuation to EPFL's DSP series. Mathematically rigorous but highly applicable.
Great course with nice examples. However I got stuck on week 3 quiz for a long time which was a little tricky, but otherwise the tests were also good and they checked the concepts well.
Sobre Programa de cursos integrados Processamento Digital de Sinais
This Specialization provides a full course in Digital Signal Processing, with a focus on audio processing and data transmission. You will start from the basic concepts of discrete-time signals and proceed to learn how to analyze data via the Fourier transform, how to manipulate data via digital filters and how to convert analog signals into digital format. Finally, you will also discover how to implement real-time DSP algorithms on a general-purpose microcontroller. The solid theoretical bases provided by the four courses in this specialization are complemented by applied examples in Python, in the form of Jupyter Notebooks; exercises with solutions provide a wealth of examples in order to tackle the weekly homework.

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