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 forma parte de Programa especializado: Procesamiento digital de señales
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Qué aprenderás
The nature of discrete-time signals
Discrete-time signals are vectors in a vector space
Discrete-time signals can be analyzed in the frequency domain via the Fourier transform
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Programa - Qué aprenderás en este curso
Module 1.1: Digital Signal Processing: the Basics
Introduction to the notation and basics of Digital Signal Processing
Module 1.2: Signal Processing Meets Vector Space
Modeling signals as vectors in an appropriate vector space. Using linear algebra to express signal manipulations.
Module 1.3: Fourier Analysis: the Basics
The fundamental concepts behind the Fourier transform and the frequency domain
Module 1.4: Fourier Analysis: More Advanced Tools
Delving deeper in the world of Fourier analysis.
Reseñas
- 5 stars70,53 %
- 4 stars19,56 %
- 3 stars5,80 %
- 2 stars1,72 %
- 1 star2,36 %
Principales reseñas sobre DIGITAL SIGNAL PROCESSING 1: BASIC CONCEPTS AND ALGORITHMS
Lecture explains concepts very clearly. Python labs provide very good hands-on experience.
The math was extremely difficult. But I made it through.
IT WAS AMAZING, I LEARNED SO MANY THINGS!!! Great job
The lectures were extremely good. Concepts were well-explained. Very engaging lessons and coursework.
Acerca de Programa especializado: Procesamiento digital de señales
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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