Catalog

Signals and Systems

Electrical Engineering and Computer Science MIT CC BY-NC-SA 4.0 26 lectures

This course was developed in 1987 by the MIT Center for Advanced Engineering Studies. It was designed as a distance-education course for engineers and scientists in the workplace. Signals and Systems is an introduction to analog and digital signal processing, a topic that forms an integral part of engineering systems in many diverse areas, including seismic data processing, communications, speech processing, image processing, defense electronics, consumer electronics, and consumer products. The course presents and integrates the basic concepts for both continuous-time and discrete-time signals and systems. Signal and system representations are developed for both time and frequency domains. These representations are related through the Fourier transform and its generalizations, which are explored in detail. Filtering and filter design, modulation, and sampling for both analog and digital systems, as well as exposition and demonstration of the basic concepts of feedback systems for both analog and digital systems, are discussed and illustrated.

Syllabus

  1. 1 Lecture 1: Introduction
  2. 2 Lecture 2: Signals and Systems: Part I
  3. 3 Lecture 3: Signals and Systems: Part II
  4. 4 Lecture 4: Convolution
  5. 5 Lecture 5: Properties of Linear, Time-Invariant Systems
  6. 6 Lecture 6: Systems Represented by Differential Equations
  7. 7 Lecture 7: Continuous-Time Fourier Series
  8. 8 Lecture 8: Continuous-Time Fourier Transform
  9. 9 Lecture 9: Fourier Transform Properties
  10. 10 Lecture 10: Discrete-Time Fourier Series
  11. 11 Lecture 11: Discrete-Time Fourier Transform
  12. 12 Lecture 12: Filtering
  13. 13 Lecture 13: Continuous-Time Modulation
  14. 14 Lecture 14: Demonstration of Amplitude Modulation
  15. 15 Lecture 15: Discrete-Time Modulation
  16. 16 Lecture 16: Sampling
  17. 17 Lecture 17: Interpolation
  18. 18 Lecture 18: Discrete-Time Processing of Continuous-Time Signals
  19. 19 Lecture 19: Discrete-Time Sampling
  20. 20 Lecture 20: The Laplace Transform
  21. 21 Lecture 21: Continuous-Time Second-Order Systems
  22. 22 Lecture 22: The z-Transform
  23. 23 Lecture 23: Mapping Continuous-Time Filters to Discrete-Time Filters
  24. 24 Lecture 24: Butterworth Filters
  25. 25 Lecture 25: Feedback
  26. 26 Lecture 26: Feedback Example: The Inverted Pendulum

Course materials