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Foundations

March 28, 2019 by 3200 Creative

The Signal Processing Foundations series of 16 lessons begins with the philosophy of the field. Next you will discover the basic notation and terminology. Signal Processing Foundations also introduces methods for describing the interaction between signals and signal-processing systems.  Understanding the philosophy of signal processing will help you later follow the context and rationale for different signal processing methods. Signal processing has developed its own language for clearly communicating important concepts; Signal Processing Foundations will teach you cornerstone vocabulary of the field. You will also be introduced to several mathematical tools for relating the input to the output of  signal-processing systems. Different tools provide different perspectives on the interaction and have different roles in signal processing.

Course Content

Lessons Status
1

Signals Everywhere

2

Ever-Present Noise

3

Models, Math, and Real-World Signals

4

Four Signal-Processing Themes

5

Building Signals with Blocks: Basis Expansions

6

Jupyter Notebook: Explore FIR Filtering

7

Jupyter Notebook: Explore Image Filtering

8

Signals: The Basics

9

Sinusoidal Signals

10

Sinusoidal Signals Examples

11

Complex Sinusoids

12

Exponential, Step, and Impulse Signals

13

Introduction to Linear, Time-Invariant Systems

14

Introduction to Difference Equation System Descriptions

15

Impulse Response Descriptions for LTI Systems

16

Frequency Response Descriptions for LTI Systems

17

Introduction to the System Function and System Poles and Zeros

18

The Four Fourier Representations

19

Summary Problems for Foundations

Filed Under: Uncategorized

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Course Lessons

  • Signals Everywhere

  • Ever-Present Noise

  • Models, Math, and Real-World Signals

  • Four Signal-Processing Themes

  • Building Signals with Blocks: Basis Expansions

  • Jupyter Notebook: Explore FIR Filtering

  • Jupyter Notebook: Explore Image Filtering

  • Signals: The Basics

  • Sinusoidal Signals

  • Sinusoidal Signals Examples

  • Complex Sinusoids

  • Exponential, Step, and Impulse Signals

  • Introduction to Linear, Time-Invariant Systems

  • Introduction to Difference Equation System Descriptions

  • Impulse Response Descriptions for LTI Systems

  • Frequency Response Descriptions for LTI Systems

  • Introduction to the System Function and System Poles and Zeros

  • The Four Fourier Representations

  • Summary Problems for Foundations

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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