Abstract

Information Theory (IT) originated in the realm of telecommunications, focusing on channel optimization and encoding. In recent decades, IT has been applied to understanding fundamental concepts in various other fields such as cognitive neuroscience, biology, and dimensionality reduction in machine learning. This short video will present how IT can help us understand fundamental aspects of measurement, such as resolution and signal chain optimization. I will also demonstrate how some results can lead to practical applications, such as the optimal choice of quantization resolution in A/D conversion for a noisy interface. The goal is for this framework to simplify design challenges in more complex contexts.

Keywords: Information theory; Theory of measurement; Analog-to-digital conversion; Signal chain optimization; Sensor design

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