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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数字信号处理 专项课程洛桑联邦理工学院课程信息
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第 2 门课程（共 4 门）
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中级
完成时间大约为18 小时
英语（English）
字幕：英语（English）
您将学到的内容有
Digital filters, how they work
Digital filter design
Adaptive signal processing
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 2 门课程（共 4 门）
可灵活调整截止日期
根据您的日程表重置截止日期。
中级
完成时间大约为18 小时
英语（English）
字幕：英语（English）
提供方
洛桑联邦理工学院
教学大纲 - 您将从这门课程中学到什么
完成时间为 7 小时
Module 2.1 Digital Filters
How digital filters work in time and in frequency.
完成时间为 7 小时
13 个视频 （总计 78 分钟）, 12 个阅读材料, 1 个测验
13 个视频
2.1.1.b Convolution6分钟
2.1.2.a The moving average filter8分钟
2.1.2.b The leaky integrator5分钟
2.1.3.a Filter classification in the time domain3分钟
2.1.3.b Filter stability5分钟
2.1.4.a The convolution theorem6分钟
2.1.4.b Examples of frequency response14分钟
2.1.5.a Filter classification in the frequency domain1分钟
2.1.5.b The ideal lowpass filter6分钟
2.1.5.c Ideal filters derived from the ideal lowpass filter2分钟
2.1.5.d Demodulation revisited2分钟
SOTD: Can one hear the shape of a room?10分钟
12 个阅读材料
Welcome to DSP Two!5分钟
Introduction1分钟
What have we learned?3分钟
Introduction1分钟
What have we learned?3分钟
Introduction1分钟
What have we learned?2分钟
Introduction2分钟
What have we learned?3分钟
Introduction2分钟
What have we learned?3分钟
Practice homework1小时
1 个练习
Homework for Module 2.12 小时 30 分
完成时间为 8 小时
Module 2.2: Filter Design
Learning how to choose and design the right filter using the z-transform and numerical tools.
完成时间为 8 小时
13 个视频 （总计 147 分钟）, 11 个阅读材料, 1 个测验
13 个视频
2.2.1.b The window method10分钟
2.2.1.c Frequency sampling2分钟
2.2.2.a The z-transform14分钟
2.2.2.b Region of convergence and stability15分钟
2.2.3 Intuitive IIR designs10分钟
2.2.4.a Filter specifications6分钟
2.2.4.b IIR design3分钟
2.2.4.c FIR design7分钟
2.2.4.d Fractional delay and Hilbert filter16分钟
2.2.5.a Implementation of digital filters12分钟
2.2.5.b Real-time processing22分钟
Signal of the Day: Image Resolution and Space Exploration19分钟
11 个阅读材料
Introduction5分钟
What have we learned?2分钟
Introduction5分钟
What have we learned?5分钟
Introduction1分钟
What have we learned?2分钟
Introduction2分钟
What have we learned?5分钟
Introduction3分钟
Practice homework1小时
Notes and Supplementary Materials3分钟
1 个练习
Homework for Module 2.21 小时 30 分
完成时间为 3 小时
Module 2.3: Stochastic and Adaptive Signal Processing
Analyzing and processing random signals and designing filters that adapt to unknown inputs.
完成时间为 3 小时
8 个视频 （总计 75 分钟）, 6 个阅读材料, 1 个测验
8 个视频
2.3.1.b Stochastic Processes10分钟
2.3.1.c Power Spectral Density18分钟
2.3.1.d Filtering Random Processes4分钟
2.3.2.a Optimal Least Squares10分钟
2.3.2.b LPC Speech Coding7分钟
2.3.2.c The LMS Filter8分钟
2.3.2.d Echo Cancellation4分钟
6 个阅读材料
Introduction8分钟
What have we learned?5分钟
Introduction3分钟
What have we learned?10分钟
Practice Homework10分钟
Notes and Supplementary Material5分钟
1 个练习
Homework for Module 2.3
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来自DIGITAL SIGNAL PROCESSING 2: FILTERING的热门评论
由 BL 提供Aug 30, 2020
Excellent continuation to EPFL's DSP series. Be aware that the 3rd week requires a good foundation in statistics.
由 PG 提供Sep 4, 2020
Add some numerical problems and solve them in your video lectures for the better understanding of concepts.
由 MC 提供Oct 7, 2020
Best material on Signal Processing. Instructors emphasized on concepts. This course is enjoyable
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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