Free hands-on course with the implementation (in Python) and description of several computational, mathematical and statistical algorithms.
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Updated
Oct 18, 2023 - HTML
Free hands-on course with the implementation (in Python) and description of several computational, mathematical and statistical algorithms.
Chaotic attractors with python (Lorenz, Rossler, Rikitake etc.)
Nonlinear time series analysis in R
Non-Linear Dynamic Systems
Generate nifty images using chaotic systems.
Package for identifying regular, complex, and stochastic behavior in timeseries
Algorithm for pseudo random bit generator using chaotic system.
Learn and model chaotic systems using Long Short-Term Memory (LSTM) networks, with a focus on the Lorenz system
A simple 2d and 3d chaos attractor visualiser written in java and libGDX
cNN-DP: Composite neural network with differential propagation for impulsive nonlinear dynamics (JCOMP 2024)
Image Encryption using GENOMICS (Central Dogma algorithm) & Chaotic system-SHA256 hashing.
A chaotic system simulator. Consists of RK4 algorithm for accurate calculations, LSTM+Transformer AI model for accurate, local, and low-latency predictions, and LLM integration via API to explain the phenomena to the user.
Especialização em Métodos Matemáticos Aplicados - UTFPR
This Matlab script & simulink defines Lorenz Attractor as it well known by chaotic system, it can be used for a lot of applications like cryptography and many more
🌌 ChaosChain-AI: Next-Gen Supply Chain AI Simulator Advanced AI control tower combining chaotic demand modeling, Monte Carlo simulations, and multi-factor risk scoring. Features real-time monitoring, predictive analytics, and automated mitigation across global supply chains. 🔬 Research | 🏭 Supply Chain AI | 🤖 Machine Learning |📊 Simulation
Rust-based project exploring chaotic systems through high-performance simulations
Chaotic Scattering with with POV-Ray
TriPendulum: A Simulation of Chaotic System
A Python implementation of a chaotic N-pendulum simulation using Lagrangian mechanics. This shows the extreme sensitivity of chaotic systems to initial conditions. Customizable node count, string count, runtime, and perturbation.
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