An OpenAI gym environment designed for the control of dynamical systems
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Updated
Apr 12, 2020 - Python
An OpenAI gym environment designed for the control of dynamical systems
Neural network that has been trained to detect temporal correlation and distinguish chaotic from stochastic signals
Here, we can find different simulations of chaotic scenarios in physics. The codes were written as part of the University dissertation and intend to visualise and provide meaningful explanation to the system's characteristics.
Lorenz attractor simulator
Fun with differential equations
A collection of programs that provide numerical solutions to and applications of differential equations, and model chaotic attractors.
A Python package to simulate and measure chaotic dynamical systems.
Bifurcation Diagrams for Discrete Time Chaotic Maps
Chaotic attractors with python (Lorenz, Rossler, Rikitake etc.)
Bifurcation Diagrams for Discrete-Time Maps in Python - https://doi.org/10.5281/zenodo.13276873
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