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Jupyter Notebook: Explore FIR Filtering

January 21, 2023 by allsignal

Original and average-filtered sections of an audio clip.

Filters are used to change the character of signals in a desired manner. This activity will give you hands-on experience with simple filters and begin developing your intuition. You will see the effect of the filter in the graph and hear the effect via audio. The design of filters for specific purposes is an extensive subject that will be pursued at a later point in your studies.

Prerequisites

Using Jupyter Notebooks

Four Signal Processing Themes

Files

Explore FIR Filtering


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Filed Under: Introductory Content

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Course Lessons

  • Signals Everywhere

  • Ever-Present Noise

  • Models, Math, and Real-World Signals

  • Four Signal-Processing Themes

  • Jupyter Notebook: Explore FIR Filtering

  • Jupyter Notebook: Explore Image Filtering

  • Building Signals with Blocks: Basis Expansions

  • 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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