Tools for the exploration of chaos and nonlinear dynamics
Strange attractors with Lyapunov exponents
Award winning software library for nonlinear dynamics and nonlinear timeseries analysis
A continuation of my gallery of three-dimensional chaotic attractors.
Gallery of more than 100 three-dimensional сhaotic attractors.
Gallery of high-dimensional hyperchaotic attractors.
A modern, high-performance Python framework designed to provide a cohesive, end-to-end environment for the study of dynamical systems.
About the https://iris.unipa.it/retrieve/handle/10447/276402/535513/81-Minati_Chaos-2017.pdf I show a set of dynamic non linear equation that represent a good approximation of autonomous chaotic oscillator circuit. Chaos is a pervasive occurrence in these kind of circuits.
MATLAB script for calculating Lyapunov exponents and Kaplan—Yorke dimension.
package for simulation and visualization of strange attractors
The Hopalong Attractor with Rust
This library instantiates an RNN to solve Newsome & Shadlin's task -- two types of input and a context to decide which to attend. It does so with an itinerating attractor network.
Chaotic attractors with python (Lorenz, Rossler, Rikitake etc.)
A Python package to simulate and measure chaotic dynamical systems.
Collection of Python Code for Creating Strange Attractors
Behavior class for BabylonJS that adds numeric values interpolation by the distance between target and attractor
Implementing Hopfield Networks from scratch, testing their content addressable memory, attractor, and energy landscape, investigating their resistance to noise, experimenting with their memory capacity, and putting strain on them with sparse patterns.
Rössler attractor solved in MATLAB using the general RK4 method.
Supplementary code for the RNN models in: "Attractor dynamics gate cortical information flow during decision-making" (2021) Arseny Finkelstein, Lorenzo Fontolan, Michael N. Economo, Nuo Li, Sandro Romani, and Karel Svoboda
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