Welcome to Multi-Component Signal Methods Benchmarks’s documentation!
A Common Framework for Benchmarking of MCS Methods
We introduce a public, open-source, Python-based toolbox for benchmarking multi-component signal analysis methods, implemented either in Python or Matlab.
The goal of this toolbox is providing the signal-processing community with a common framework that allows researcher-independent comparisons between methods and favors reproducible research.
Contents:
Examples:
mcsm-benchs: Creating benchmarks of MCS Methodsmcsm-benchs: Exploring signals provided by the SignalBank classmcsm-benchs: Benchmarking methods for signal detectionmcsm-benchs: Benchmarks with personalized noise-generating functionsmcsm-benchs: Querying Signal class attributes for more versatile benchmarksmcsm-benchs: Benchmarking methods for instantaneous frequency estimationmcsm-benchs: Benchmarking methods for component retrievalmcsm-benchs: Using user-provided signals and performance metric