Digital Signal Processing 1: Basic Concepts and Algorithms from Coursera

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.

In this series of four courses, you will 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.

What's inside

Syllabus

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.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches core concepts behind Fourier analysis and its applications, such as frequency domain and digital signal processing

Suitable for learners with basic calculus and linear algebra knowledge

Provides theoretical explanations along with practical hands-on examples and demonstrations, facilitating understanding and application

Instructed by Paolo Prandoni and Martin Vetterli, renowned in the field

Designed to build a solid DSP toolset from the ground up, making it accessible to beginners

Recommended for individuals seeking to enhance their understanding and skills in digital signal processing

Reviews summary

Well-received dsp course with a mathematical focus

Learners say this intermediate course on digital signal processing is well received and largely positive, earning high ratings and positive reviews. Students found the lectures engaging and the instructors knowledgeable. The course emphasizes mathematical rigor but also provides intuitive explanations. The quizzes and homeworks are challenging but fair, and the Python notebooks are a valuable resource. However, students note that the course requires a strong math background and that the video lectures can sometimes be difficult to follow. Overall, this course is highly recommended for those with a strong math background who are looking for a mathematically rigorous introduction to digital signal processing.

Course places emphasis on mathematical rigor.

"The problems and quizzes were difficult but very standard."

"The course instructors are really good at delivering the concepts intuitively and it does not fall short of providing mathematical derivations as well."

Quizzes and homeworks are challenging but fair.

"The problems and quizzes were difficult but very standard."

"The course is very well-organized and the instructors propose extra resources, which I very appreciate."

Lectures are engaging and easy to understand.

"The lectures were extremely good."

"The lectures are excellent. The videos, slides, exercises are high quality."

Video lectures can be difficult to follow.

"The video lectures are great, but the quizes are awful."

"I can watch the videos multiple times, but i don't want to because they are boring."

Requires a strong math background.

"It is a complex course, you should refresh your calculus knowledge before starting it."

"The expectation is that you are an expert in both calculus and linear algebra"

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Digital Signal Processing 1: Basic Concepts and Algorithms with these activities:

Fourier transform review

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Review the basics of the Fourier transform to strengthen your understanding of frequency domain analysis.

Browse courses on Fourier Transform

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Revisit the definition of the Fourier transform and its inverse.
Practice applying the Fourier transform to simple signals.
Explore the properties of the Fourier transform, such as linearity and time-shifting.

Sampling and interpolation exercises

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Solve practice problems on sampling and interpolation to enhance your understanding of these techniques.

Browse courses on Sampling

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Calculate the sampling rate required to avoid aliasing for a given signal.
Apply different interpolation methods to resample a signal.

Filter design tutorials

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Follow online tutorials to learn about different filter design techniques and their applications.

Browse courses on Filter Design

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Explore different filter design methods, such as FIR and IIR filters.
Implement filter design algorithms using appropriate software tools.

One other activity

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Show all four activities

Signal processing project

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Design and implement a digital signal processing algorithm to solve a practical problem, such as noise reduction or feature extraction.

Browse courses on Signal Processing

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Identify a signal processing problem to solve.
Design and implement a DSP algorithm to address the problem.
Evaluate the performance of your algorithm using appropriate metrics.

Career center

Learners who complete Digital Signal Processing 1: Basic Concepts and Algorithms will develop knowledge and skills that may be useful to these careers:

DSP Software Engineer

A DSP Software Engineer designs, develops, and tests software for digital signal processing systems. This course provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to the design and development of DSP software.

See salaries and explore the career path for DSP Software Engineer

Signal Processing Researcher

A Signal Processing Researcher conducts research in signal processing and develops new signal processing techniques. This course provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to research in signal processing.

See salaries and explore the career path for Signal Processing Researcher

Digital Signal Processing Engineer

A Digital Signal Processing Engineer designs, develops, and tests digital signal processing systems. This course provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to the design and development of digital signal processing systems.

See salaries and explore the career path for Digital Signal Processing Engineer

Multimedia Signal Processing Engineer

A Multimedia Signal Processing Engineer designs, develops, and tests multimedia signal processing systems. This course provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to the design and development of multimedia signal processing systems.

See salaries and explore the career path for Multimedia Signal Processing Engineer

Communications Engineer

A Communications Engineer designs, develops, and maintains communications systems. This course may be helpful because it provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to the design and development of communications systems.

See salaries and explore the career path for Communications Engineer

Embedded Systems Engineer

An Embedded Systems Engineer designs, develops, and tests embedded systems. This course may be helpful because it provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to the design and development of embedded systems.

See salaries and explore the career path for Embedded Systems Engineer

Audio Signal Processing Engineer

An Audio Signal Processing Engineer designs, develops, and tests audio signal processing systems. This course may be helpful because it provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to the design and development of audio signal processing systems.

See salaries and explore the career path for Audio Signal Processing Engineer

Data Scientist

A Data Scientist collects, analyzes, and interprets data to extract meaningful insights. This course may be helpful because it provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to the analysis and interpretation of data.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

A Machine Learning Engineer designs, develops, and tests machine learning systems. This course may be helpful because it provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to the design and development of machine learning systems.

See salaries and explore the career path for Machine Learning Engineer

Software Engineer

A Software Engineer designs, develops, and tests software systems. This course may be helpful because it provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to the design and development of software systems.

See salaries and explore the career path for Software Engineer

Electrical Engineer

An Electrical Engineer designs, develops, and tests electrical systems. This course may be helpful because it provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to the design and development of electrical systems.

See salaries and explore the career path for Electrical Engineer

Systems Engineer

A Systems Engineer designs, develops, and tests systems. This course may be helpful because it provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to the design and development of systems.

See salaries and explore the career path for Systems Engineer

Physicist

A Physicist conducts research in physics and develops new physical theories and techniques. This course may be helpful because it provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to research in physics.

See salaries and explore the career path for Physicist

Mathematician

A Mathematician conducts research in mathematics and develops new mathematical theories and techniques. This course may be helpful because it provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to research in mathematics.

See salaries and explore the career path for Mathematician

Operations Research Analyst

An Operations Research Analyst applies mathematical and analytical techniques to solve problems in business and industry. This course may be helpful because it provides a foundation in the fundamentals of Digital Signal Processing, including Fourier analysis and filter design. This knowledge can be applied to the analysis and solution of problems in business and industry.

See salaries and explore the career path for Operations Research Analyst