quantization-and-sampling.md

layout	default
title	L1: Quantization and Sampling
description	Digitize analog signals by exploring quantization levels and sampling rates on real audio, plus the Nyquist theorem and aliasing through hands-on Python plots.
parent	Signal Processing
grand_parent	Signals
has_toc	false
comments	false

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This Notebook introduces the two primary factors in digitizing an analog signal: quantization and sampling. Describes and shows the effect of different quantization levels and sampling rates on real signals (audio data) and introduces the Nyquist sampling theorem, aliasing, and some frequency plots.

You can view the Notebook in html here but we also strongly recommend working with our Notebooks locally by performing a git clone on https://github.com/makeabilitylab/signals.git and running the Jupyter Notebook on your system (see installation notes).

Next Lesson

In the next lesson, you'll learn techniques to compare signals in the time domain, including Euclidean distance, cross-correlation, and Dynamic Time Warping (DTW).

Next Lesson →

Comparing Signals in the Time Domain