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Time Domain LTI Systems

March 26, 2019 by 3200 Creative

This series of lessons builds on several of the concepts introduced in the Foundations series. It concerns time-domain descriptions for the characteristics of linear, time-invariant (LTI) systems. You will learn the origins and properties of convolution for describing LTI systems in terms of the impulse response and a procedure for evaluating convolution. You will also learn how differential and difference equations are used to represent LTI systems and what they reveal about system behavior. If you have no prior experience with LTI systems, then this series is designed to efficiently teach you the knowledge you need for future study.

Course Content

Lessons Status
1

Impulse Response and LTI Systems - Part II

2

Graphical Evaluation of Discrete-Time Convolution

3

Graphical Evaluation of Continuous-Time Convolution

4

Difference Equations: Solving System Responses with Stored Energy

5

Characteristics of Systems Described by Difference Equations

6

Differential Equations: Solving System Responses with Stored Energy

7

Characteristics of Systems Described by Differential Equations

8

Two-Dimensional Signal Processing: Discrete Space

9

Problems for Time Domain LTI Systems

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Course Lessons

  • Impulse Response and LTI Systems – Part II

  • Graphical Evaluation of Discrete-Time Convolution

  • Graphical Evaluation of Continuous-Time Convolution

  • Difference Equations: Solving System Responses with Stored Energy

  • Characteristics of Systems Described by Difference Equations

  • Differential Equations: Solving System Responses with Stored Energy

  • Characteristics of Systems Described by Differential Equations

  • Two-Dimensional Signal Processing: Discrete Space

  • Problems for Time Domain LTI Systems

Courses

  • Foundations

  • Time Domain LTI Systems

  • Fourier Series and Transforms

  • Sampling and Reconstruction

  • The DFT and Applications

  • The Z-Transform

  • Intro to Filter Design

  • IIR Filter Design

  • FIR Filter Design

  • Random Signal Characterization

  • Basis Representations of Signals

  • Estimation of Power Spectra and Coherence

  • Introduction to Signal Estimation and Detection Theory

  • MMSE Filtering and Least-Squares Problems

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