Bifurcation Diagram of 3D Chaotic Systems
Program for generating bifurcation diagrams of 3D chaotic systems, useful for adjusting and analyzing chaotic bifurcation patterns with code implementation details
Explore MATLAB source code curated for "分岔图" with clean implementations, documentation, and examples.
Program for generating bifurcation diagrams of 3D chaotic systems, useful for adjusting and analyzing chaotic bifurcation patterns with code implementation details
This source code generates a bifurcation diagram for chaos theory, demonstrating the transition from orderly behavior to chaotic dynamics through parameter variation. The implementation allows analysis of dynamical system characteristics using numerical simulation approaches with adjustable control parameters and iterative mapping functions.
File: C-C method for computing time delay and embedding dimension - Implements the C-C algorithm to determine optimal time delay and embedding dimension for phase space reconstruction. File: dingyi_lyapunov - Computes Lyapunov exponents using the definition method. File: fencha - Generates bifurcation diagrams for Lorenz systems using the regional maximum method. File: m_test - Solves for embedding dimension m. File: pinghengdian
Comprehensive analysis of bifurcation diagram solutions for hyperchaotic systems, featuring detailed explanations and enhanced code implementation approaches for better readability and understanding
Implementation of bifurcation diagram plotting for chaotic systems during the transition from small periodic states to chaotic states using MATLAB
This collection features multiple bifurcation diagrams of the Lorenz system, accompanied by several methodologies for generating bifurcation diagrams, including code implementation approaches and parameter variation techniques.
This is a bifurcation diagram illustrating the bifurcation behavior of a pendulum model, which I have carefully preserved and am sharing for reference and further analysis.
A highly practical MATLAB program for generating bifurcation diagrams with valuable reference implementation for dynamic systems analysis.
This assignment from our nonlinear dynamics course demonstrates key concepts including bifurcation diagrams, cobweb plots, and Poincaré sections with implementable code approaches. The resources provide practical insights into analyzing nonlinear systems through numerical methods and visualization techniques.
A Python program for generating Logistic Map bifurcation diagrams, demonstrating unique chaotic behavior distinct from conventional nonlinear systems. The mapping follows the equation: xₙ = 1 - a·xₙ₋₁², where parameter a ranges between 0 and 2. The implementation iterates through parameter values, discarding transients before plotting asymptotic behavior.