Digital Signal Processing 2: Filtering

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Paolo Prandoni 另外 +1 位授课教师

提供方

课程信息

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. 
The goal, for students of this course, will be to 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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第 2 门课程（共 4 门）

数字信号处理专项课程

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：阿拉伯语（Arabic）, 法语（French）, （欧洲人讲的）葡萄牙语, 意大利语, 越南语, 德语（German）, 俄语（Russian）, 英语（English）, 西班牙语（Spanish）

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）

数字信号处理专项课程

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）

讲师

授课教师评分

4.82/5 （28 个评分）

Paolo Prandoni

Lecturer

School of Computer and Communication Science

89,111 个学生

5 门课程

Martin Vetterli

Professor

School of Computer and Communication Sciences

89,111 个学生

5 门课程

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

周

周 1

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.a Linear time-invariant filters4分钟

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

周

周 2

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.a Impulse truncation (and the Gibbs phenomenon)3分钟

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

周

周 3

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.a Random Variables10分钟

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

由 MW 提供Nov 27, 2020

This is a really good course that has very good exercises

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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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Digital Signal Processing 2: Filtering