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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Acerca de este Curso
Qué aprenderás
Digital filters, how they work
Digital filter design
Adaptive signal processing
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Programa - Qué aprenderás en este curso
Module 2.1 Digital Filters
How digital filters work in time and in frequency.
Module 2.2: Filter Design
Learning how to choose and design the right filter using the z-transform and numerical tools.
Module 2.3: Stochastic and Adaptive Signal Processing
Analyzing and processing random signals and designing filters that adapt to unknown inputs.
Reseñas
- 5 stars81,20 %
- 4 stars12,08 %
- 3 stars3,35 %
- 2 stars2,01 %
- 1 star1,34 %
Principales reseñas sobre DIGITAL SIGNAL PROCESSING 2: FILTERING
Had to use a lot of outside material - mostly YouTube videos from Rich Radke and Barry Van Veen to complete this course.
Add some numerical problems and solve them in your video lectures for the better understanding of concepts.
Best material on Signal Processing. Instructors emphasized on concepts. This course is enjoyable
This is a really good course that has very good exercises
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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