{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "
" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "\n", "\n", "\n", "To study musical structures and their mutual relations, one general idea is to convert the music signal into a suitable feature sequence and then to compare each element of the feature sequence with all other elements of the sequence. This results in a self-similarity matrix (SSM), a tool which is of fundamental importance not only for music structure analysis but also for the analysis of many kinds of time series. Following Section 4.2.1 of [Müller, FMP, Springer 2015], we introduce in this notebook the concept of SSMs and discuss their fundamental properties. For a more practical approach to this topic, we refer to the FMP notebook on synthetic generation of SSMs.\n", "\n", "
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