Analysis of Signals and Systems

Course #EC2410

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Clock Est. completion in 3 months

Location pin Offered through Distance Learning

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Overview

Analysis of digital and analog signals in the frequency domain; properties and applications of the discrete Fourier transform, the Fourier series, and the continuous Fourier transform; analysis of continuous systems using convolution and frequency domain methods; applications to sampling, windowing, and amplitude modulation and demodulation systems.

Prerequisites

  • MA1113

Learning Outcomes

Given a continuous signal, determine the effects of sampling in time. Be able to define the minimum sampling frequency to avoid aliasing when discretizing a continuous signal Given a dynamic system, determine if it is Linear Time Invariant (LTI); Given a LTI system, compute the response by convolution; Given a periodic signal, determine its Fourier Series expansion; Given a continuous time signal, compute its Fourier Transform; Given a continuous time signal, compute the Fourier Transform using the tables and the properties; Given a system, characterize it in terms of its frequency response; Apply the properties of the Fourier Transform to basic modulation and demodulation problems; Develop the ability to recognize and characterize simple discrete random processes in the time domain. Learn to be able to fully characterize stationary discrete random processes from a second moment viewpoint in the time domain and frequency domains. Develop an understanding for Gaussian white noise for 1- and N-dimensional random vectors. Learn to characterize random signals from a second moment viewpoint as they are processed through discrete linear systems. Also learn to characterize simple linear transformations for continuous signals in time and frequency domains. Learn how to deal with uncertainty in estimated parameters via confidence intervals.

Other Information

Ability to program in MATLAB is required.