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.
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课程信息
您将学到的内容有
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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洛桑联邦理工学院
教学大纲 - 您将从这门课程中学到什么
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.
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来自DIGITAL SIGNAL PROCESSING 1: BASIC CONCEPTS AND ALGORITHMS的热门评论
Such a wonderful course, great instructors, and well structured. However, a little bit too involved and the concepts can be a little tricky to comprehend at times.
It offers rigorous introduction to DSP. Besides the lectures, it requires separate study of the materials to get well acquainted with the concepts.
If you have enough patience to go through the math, you'll find this course and the subsequent courses in the specialization extremely rewarding.
Excellent first look into DSP, especially in the context of Fourier. Fairly math heavy so a strong math background is recommended.
关于 数字信号处理 专项课程
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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