The Shannon entropy tool is a Julia-based custom instrument that calculates the Shannon entropy of a signal. The result is displayed as a single numeric value in an instrument window.

Shannon entropy is a measure of the randomness or complexity of a signal. It is based on the probability distribution of signal values and quantifies the average information content.

Background and usage:

Entropy is widely used in signal processing and data analysis to characterize signals:

•Low entropy indicates a more regular, predictable, or periodic signal

•High entropy indicates a more random or noise-like signal

Typical applications include:

•Detecting changes in signal complexity over time

•Identifying transitions between structured and noisy signal segments

•Feature extraction for classification or machine learning tasks

•Monitoring system behavior or fault detection

As a custom instrument, the Shannon entropy tool can be combined with other SIGVIEW functions, such as tracking instrument values over time or integrating into automated analysis workflows.