Digital Signal Processing 4: Applications
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.
Monthly Subscription Starting at AED 99 + VAT
- Level Professional
- المدة 14 ساعات hours
- الطبع بواسطة École Polytechnique Fédérale de Lausanne
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Offered by
عن
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.الوحدات
Welcome to DSP Four!
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1
Readings
1
Readings
- Welcome to DSP Four!
Lesson 4.1.1: Image processing basics
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2
Videos
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1
Readings
2
Videos
- 4.1.1.a Notation and key concepts
- 4.1.1.b Image manipulations
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Readings
- Introduction
Lesson 4.1.2: Frequency analysis
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1
Videos
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1
Readings
1
Videos
- 4.1.2 Frequency analysis
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Readings
- Introduction
Lesson 4.1.3: Image Filtering
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2
Videos
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1
Readings
2
Videos
- 4.1.3.a 2D Filters
- 4.1.3.b Classic Filters for Images
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Readings
- Introduction
Lesson 4.1.4: Image compression
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2
Videos
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1
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2
Videos
- 4.1.4.a Image compression
- 4.1.4.b The JPEG compression algorithm
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Readings
- Introduction
Assignments
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1
Readings
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1
Assignment
1
Assignment
- Homework for Module 4.1
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Readings
- Practice Homework
Additional Resources
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1
Videos
1
Videos
- Signal of the Day: Moire Patterns
Python Notebook
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1
Plugin
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1
Lab
1
Labs
- Haar Bases for Image Compression
Lesson 4.2.1: Introduction to digital communication systems
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3
Videos
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2
Readings
3
Videos
- 4.2.1.a The success factors for digital communications
- 4.2.1.b The analog channel constraints
- 4.2.1.c The design problem
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Readings
- Introduction
- What have we learned?
Lesson 4.2.2: Controlling bandwidth and power
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4
Videos
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2
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4
Videos
- 4.2.2.a Upsampling
- 4.2.2.b Fitting the transmitter spectrum
- 4.2.2.c Noise and probability of error
- 4.2.2.d PAM and QAM
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Readings
- Introduction
- What have we learned?
Lesson 4.2.3: Transmitter and Receiver
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5
Videos
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2
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5
Videos
- 4.2.3.a Modulation and demodulation
- 4.2.3.b Design example
- 4.2.3.c Receiver design
- 4.2.3.d Delay compensation
- 4.2.3.e Adaptive equalization
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Readings
- Introduction
- What have we learned?
Lesson 4.2.4: ADSL
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2
Videos
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2
Readings
2
Videos
- 4.2.4.a ADSL design
- 4.2.4.b Discrete multitone modulation
2
Readings
- Introduction
- What have we learned?
Assignments
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1
Readings
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1
Assignment
1
Assignment
- Homework for Module 4.2
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Readings
- Practice homework
Additional Resources
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1
Readings
1
Readings
- Further reading
Python Notebooks
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1
Plugin
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2
Lab
2
Labs
- The Telephone Channel
- Simple Data Transmission
Lesson 4.3.1 Hardware Lab
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1
Readings
1
Readings
- Introduction
Python Notebook
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1
Readings
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1
Lab
1
Labs
- Voice Transformers
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Readings
- The "Voice Transformer" Notebook
The Lab Videos
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4
Videos
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3
Readings
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1
Plugin
4
Videos
- Breakout board assembly
- Wiring up everything
- Oscilloscope overview, analog mode
- Oscilloscope overview, digital mode
3
Readings
- Prepare the breakout boards
- Introduction
- Introduction
Auto Summary
Digital Signal Processing 4: Applications is a comprehensive course offered under the Science & Engineering domain, designed to equip learners with a deep understanding of Digital Signal Processing (DSP). This course delves into the core principles of DSP, covering essential topics such as discrete-time signals, Fourier analysis, filter design, sampling, interpolation, and quantization. By integrating these concepts, students will develop a robust DSP toolkit, enabling them to analyze and understand practical communication systems. Led by experienced instructors from Coursera, the course emphasizes the practical application of theoretical knowledge through hands-on examples and demonstrations. Learners will have the opportunity to bridge the gap between theory and practice, enhancing their skills in analyzing and designing DSP systems. With a total duration of 840 hours, this professional-level course is ideal for individuals with a solid foundation in basic calculus and linear algebra. Participants will benefit from programming examples provided in Python notebooks, but they are also encouraged to use their preferred programming languages to experiment with the algorithms presented. Subscription options include Starter and Professional plans, making the course accessible to a wide range of learners. Whether you are a professional looking to deepen your expertise in DSP or an enthusiast aiming to explore the digital revolution's impact on communication and entertainment technologies, this course offers valuable insights and practical knowledge to advance your understanding and skills in Digital Signal Processing.
Paolo Prandoni
Martin Vetterli