lmlib Documentation

Version: 2.1.1 CFR 1 (Documentation: Nov 16, 2022) — Open-Source and for Python.

This is the official documentation for lmlib, a signal processing library to efficiently analyze single- and multi-channel time series.

This library implements Recurisve Least Squares (RLS) algorithms with

• Windowed Linear State-Space Models (Package lmlib.statespace)

• Continuous-Time Polynomial Signal Models (Package lmlib.polynomial)

This library provides methods for

• Recursive, Linear Filters,

• Shape Detection,

• Event Detection,

• Correlation, Convolution, and Matched Filters in low-dimensional vector spaces,

• and others.

This library is the result of many years of research documented in various publications (see Bibliography).

lmlib Doc Content

• API Reference
  • Packages & Modules
  • Modules Attributes
• Coding
  • ALSSMs & Cost Functions
  • Backend Selection (Plain Python vs. JIT)
  • Polynomials Basics
• Examples
  • ALSSM Signal Filters
  • Onset and Peak Detection With Two-Sided Line Models (TSLMs)
  • Advanced Event Detection with ALSSMs
  • Correlation (or Convolution) and Matched Filters
  • Calculus and Cost Functions
  • Localized Polynomials
• Signal Catalog
  • Functions
  • Signals
• Install
  • pip
  • conda
• About Us
  • Institutes
  • Software Authors
  • Research
  • Contact
• Bibliography

Indices and tables

• Index

• Module Index

• Search Page

The library is provided by ETH, FHNW, and BFH, see About Us.

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API Reference