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IITBombay: Signals and Systems, Part 1

This course provides the basic toolkit for any signal processing application - the abstraction of signals and systems, from the point of view of analysis and characterization.
10 weeks
4–6 hours per week
Instructor-led on a course schedule

About this course

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We encounter signals and systems extensively in our day-to-day lives, from making a phone call, listening to a song, editing photos, manipulating audio files, using speech recognition softwares like Siri and Google now, to taking EEGs, ECGs and X-Ray images. Each of these involves gathering, storing, transmitting and processing information from the physical world. This course will equip you to deal with these tasks efficiently by learning the basic mathematical framework of signals and systems.

This course is divided into two parts. In this part (EE210.1x), we will explore the various properties of signals and systems, characterization of Linear Shift Invariant Systems, convolution and Fourier Transform, while the next part (EE210.2x), will deal with the Sampling theorem, Z-Transform, discrete Fourier transform and Laplace transform. Ideas introduced in this course will be useful in understanding further electrical engineering courses which deal with control systems, communication systems, power systems, digital signal processing, statistical signal analysis and digital message transmission. The concepts taught in this course are also useful to students of other disciplines like mechanical, chemical, aerospace and other branches of engineering and science.

At a glance

  • Institution: IITBombayX
  • Subject: Engineering
  • Level: Intermediate
  • Prerequisites:
    High school mathematics: Sequence and series, algebra of complex numbers, basic trigonometry. Calculus: Differential and Integral calculus (single variable). Knowledge of differential equations is helpful but not required. Corequisites: Basic circuit analysis - ohm's law, KVL, KCL
  • Language: English
  • Video Transcript: English
  • Associated skills: Electroencephalography, Telecommunications, Electrical Engineering, Digital Signal Processing, Electric Power Systems, Laplace Transform, Control Systems, Speech Recognition Software, Signal Processing, Editing, Computer Control Systems, Statistical Signal Processing, Fourier Transform

What you'll learn

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  • How to unite abstractions for several kinds of systems, to draw a common system description
  • How to identify properties that this system has or does not have
  • How to deal with an important class of systems namely, linear shift invariant systems
  • How to represent and analyze signals and systems in the Fourier domain

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