Digital Signal Processing 3: Analog vs Digital
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Course Summary
This course covers advanced topics in digital signal processing, including adaptive filters, multirate processing, and statistical signal processing.Key Learning Points
- Learn how to design and implement adaptive filters for noise reduction and channel equalization.
- Understand the principles of multirate processing and how to apply it to digital signal processing systems.
- Gain knowledge of statistical signal processing and its applications in speech and image processing.
Related Topics for further study
- Adaptive Filters
- Multirate Processing
- Statistical Signal Processing
- Noise Reduction
- Channel Equalization
Learning Outcomes
- Ability to design and implement adaptive filters for noise reduction and channel equalization
- Understanding of multirate processing and its applications in digital signal processing systems
- Knowledge of statistical signal processing and its applications in speech and image processing
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of digital signal processing
- Familiarity with MATLAB or equivalent programming language
Course Difficulty Level
AdvancedCourse Format
- Online
- Self-paced
Similar Courses
- Digital Signal Processing
- Digital Signal Processing Basics
- Audio Signal Processing for Music Applications
Related Education Paths
Notable People in This Field
- Professor of Electrical and Computer Engineering
- Professor of Electrical Engineering and Computer Science
Related Books
Description
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.
Knowledge
- The difference between continuous and discrete time
- Sampling and interpolation
- Quantization, A/D and D/A converters
- Multirate signal processing
Outline
- Module 3.1: Interpolation and Sampling
- 3.1.1.a The continuous-time paradigm
- 3.1.1.b Continuous-time signal processing
- 3.1.1.c Bandlimited functions
- 3.1.2.a Polynomial interpolation
- 3.1.2.b Local interpolation
- 3.2.1.c Sinc interpolation
- 3.1.3.a The spectrum of interpolated signals
- 3.1.3.b The space of bandlimited functions
- 3.1.3.c The sampling theorem
- Signal of the Day: Fukushima
- Welcome to DSP Three!
- Introduction
- What have we learned?
- Introduction
- What have we learned?
- Introduction
- What have we learned?
- Practice homework
- Further reading
- Homework for Module 3.1
- Module 3.2: Aliasing
- 3.2.1.a Raw sampling
- 3.2.1.b Sinusoidal aliasing
- 3.2.1.c Aliasing for arbitrary spectra
- 3.2.2.a Sampling strategies
- 3.2.2.b Bandpass sampling
- Introduction
- What have we learned?
- Introduction
- Practice homework
- Homework for Module 3.2
- Module 3.3: Multirate Signal Processing
- 3.3.1.a Upsampling
- 3.3.1.b Downsampling
- 3.3.2 FIR-based sampling rate conversion
- Introduction
- What have we learned?
- Practice Homework
- Homework for Module 3.4
- Module 3:4: A/D and D/A Conversion
- 3.4.1.a Quantization
- 3.4.1.b Clipping, saturation and companding
- 3.4.2 Analog-to-digital and digital-to-analog converters
- 3.4.3.a Practical sampling and interpolation
- 3.4.3.b Oversampled D/A
- 3.4.3.c Oversampled A/D
- MP3 Compression
- Signal of the Day: Lehman Brothers
- Introduction
- What have we learned?
- Introduction
- Introduction
- What have we learned?
- Practice homework for Module 3.4
- Homework for Module 3.4
Summary of User Reviews
Learn Digital Signal Processing from top-rated instructors. This course is highly recommended by many students who have found it to be comprehensive and engaging. The course covers a range of topics and provides a good balance of theory and practice.Key Aspect Users Liked About This Course
Many users appreciated the clear and concise explanations provided by the instructors.Pros from User Reviews
- Comprehensive course content
- Engaging lectures and exercises
- Highly knowledgeable instructors
- Good balance of theory and practice
- Great value for the price
Cons from User Reviews
- Some users found the pace of the course to be too fast
- The course could benefit from more hands-on projects
- Occasional technical issues with video lectures
- The course may not be suitable for beginners
- Some users found the quizzes to be too challenging
Paolo Prandoni
4.8 Raiting
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