About This Course

Offered by MIT, Signals and Systems provides both a theoretical and practical foundation for the analysis of continuous-time and discrete-time signals and systems. It covers signal processing techniques that play a critical role in numerous fields such as electrical and electronics engineering, communications, image processing, audio processing, defense industries, and consumer electronics.

The course begins with time-domain and frequency-domain representations of signals and systems, and examines in detail the relationships between these representations through the Fourier transform and its generalizations. Concepts such as sampling, modulation, filtering, and feedback in continuous and discrete-time systems are introduced through both theoretical explanations and practical examples.

The content builds a bridge between mathematical representations of signals and real engineering applications. Students gain a conceptual understanding of system analysis while learning how to structure solutions to signal processing problems. Through visual materials and simulation-supported instruction, the course aims to make abstract concepts intuitively understandable.

Prerequisites

Participants are recommended to have basic knowledge of mathematical analysis (particularly differential equations and complex numbers) and familiarity with fundamental signal processing concepts.

Instructor

Prof. Alan V. Oppenheim, a world-renowned scholar in the Department of Electrical Engineering and Computer Science at the Massachusetts Institute of Technology (MIT), is one of the leading figures in digital signal processing. His pioneering work has had a significant impact across both academic and industrial communities.

Oppenheim’s teaching approach is distinguished by his ability to present complex technical topics in a clear, intuitive, and visually supported manner. In this course, students have the opportunity to learn the core principles of the field directly from one of its foundational contributors.