Voltar para Digital Signal Processing 1: Basic Concepts and Algorithms

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7 avaliações

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.
In this series of four courses, you will learn the fundamentals of Digital Signal Processing from the ground up. Starting from the basic definition of a discrete-time signal, we will work our way through Fourier analysis, filter design, sampling, interpolation and quantization to build a DSP toolset complete enough to analyze a practical communication system in detail. Hands-on examples and demonstration will be routinely used to close the gap between theory and practice.
To make the best of this class, it is recommended that you are proficient in basic calculus and linear algebra; several programming examples will be provided in the form of Python notebooks but you can use your favorite programming language to test the algorithms described in the course....

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por Prakriti M

•Jun 06, 2020

The lectures were extremely good. Concepts were well-explained. Very engaging lessons and coursework.

por Aditya S J

•May 14, 2020

excellent and worthy

por S J T

•Jun 06, 2020

Excellent Course.

por Carl J

•Jun 07, 2020

Nice Course, lots of applications. math is challenging when proving a problem. But it is a great course to start up. i would integrate more the programming component in class although there are Python Notes in IPython.

por saiteja

•May 16, 2020

excellence is synonym of this course

por Siddharth J

•May 26, 2020

good course

por Fernando D P

•Jul 01, 2020

It is a complex course, you should refresh your calculus knowledge before starting it. I was looking for a practical approach, the course has python notebook but I still missed practical content, with real examples and put aside formulas and analytical expressions.