A data-driven method to calculate the Lyapunov exponent of a dynamical system employing a GRU-RNN.

This is our standard library for nonlinear analysis. Many of these functions are the same we use in our services. We do have additional methods that are not public but could be made available in a future release. If you are interested in learning more, attending our workshops or webinars or using our data analysis services please contact bmchnon…

Non-Linear Dynamic Systems

Python toolbox to detect limit cycles and asses their stability

Official source code of Arrhythmia Detection

Files related to my Summer of Science Report on Nonlinear Dynamics

Python package to compute Lyapunov exponents, covariant Lyapunov vectors (CLV) and adjoints of a dynamical systems.

Evaluate the Lyapunov Spectrum of a dynamical system described by ODEs (in Python)

Calculation and visualization of average maximum lyapunov exponent for a double pendulum system

Repository for STPDP and SSRPC

Project for the Quantum Information and Computing course, 2020/2021

Lyapunov Cycle Detector is a collection of algorithms destined to study the basins of attraction of rational maps (that is, the Fatou and Julia sets). In particular, the main focus of LCD is in the detection of attracting n-cycles of said rational map and in computing its basins.

Coupled linear ODEs to model relationship dynamics

A Python package to simulate and measure chaotic dynamical systems.

For a given recurrence relation and sequence, the code outputs the corresponding Lyapunov diagram which holds key information about the stability of the generated sequence.

Fortran90 examples of Dynamic Systems

Solución numérica de la dinámica de una cosmología de Robertson-Walker, además se puede generar graficas de dicha dinámica, las secciones de Poincare, los exponentes de Lyapunov y las orbitas del sistema.

Compute Lyapunov exponents and Covariant-Lyapunov-Vectors of an RNN update trajectory

Análisis No Lineal de caoticidad en virus covid-19

Resolução da Lista 7 da disciplina FM-223: Dinâmica não-linear e caos I