Signals and Systems: From Basics to Advance
Signals and Systems
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.
What Will You Learn?
- Be familiar with commonly used signals such as the unit step, ramp, impulse function, sinusoidal signals and complex exponentials.
- Be able to classify signals as continuous-time vs. discrete-time, periodic vs. non-periodic, energy signal vs. power signal, odd vs. even, conjugate symmetric vs anti-symmetric
- Be able to describe signals mathematically and understand how to perform mathematical operations on signals.
- Be able to compute the Fourier series or Fourier transform of a set of well-defined signals from first principles. Further, be able to use the properties of the Fourier transform to compute the Fourier transform (and its inverse) for a broader class of signals.
- Understand the application of Fourier analysis to ideal filtering.
Signals and Systems: Part I43:31
Signals and Systems: Part II00:00
Properties of Linear, Time-Invariant Systems41:08
Systems Represented by Differential Equations41:27
Continuous-Time Fourier Series48:21
Continuous-Time Fourier Transform41:32
Fourier Transform Properties41:44
Discrete-Time Fourier Series47:27
Discrete-Time Fourier Transform51:26
Demonstration of Amplitude Modulation00:00
Discrete-Time Processing of Continuous-Time Signals00:00
The Laplace Transform00:00
Continuous-Time Second-Order Systems00:00
Mapping Continuous-Time Filters to Discrete-Time Filters00:00
Feedback Example: The Inverted Pendulum00:00