Adaptive Increased-Order Generalized Synchronization for Hindmarsh-Rose Neurons

Code for the adaptive control and NG-RC surrogate modeling of increased-order generalized synchronization (IOGS) between a 4D memristive Hindmarsh-Rose drive system and a controlled 5D response system with parameter uncertainty.

Requirements

Python 3.11+ (uses the standard library tomllib). Install dependencies with:

pip install -r requirements.txt

Structure

• models/ - drive system, nonlinear synchronization map, controllers, and adaptive update laws.
• simulation/ - closed-loop ODE integration of the full drive-response-adaptation system.
• ngrc/ - Next-Generation Reservoir Computing model and Bayesian optimization for hyperparameter search.
• scripts/experiments/ - entrypoints that produce cached results: verify_iogs.py (adaptive IOGS verification) and learn_manifold_coupled.py (NG-RC surrogate for the synchronization map).
• scripts/visualize/ - figure generation from cached results.
• results/ - cached .npz outputs from experiment scripts.
• plots/ - generated figures.
• config.toml - system and simulation parameters.
• paths.py - shared output-directory constants.

Reproducing results

python3 scripts/experiments/verify_iogs.py
python3 scripts/experiments/learn_manifold_coupled.py

Each writes its results to results/.