Generating Lorenz Time Series Using Equations
Producing Lorenz time series through mathematical equations proves highly valuable for studying chaotic systems and nonlinear dynamics
Explore MATLAB source code curated for "Lorenz" with clean implementations, documentation, and examples.
Producing Lorenz time series through mathematical equations proves highly valuable for studying chaotic systems and nonlinear dynamics
Lorenz Chaotic Dynamical System Analysis Source Code including system trajectories and attractors - featuring complete MATLAB/Octave implementation with visualization capabilities
MATLAB demonstration programs implementing chaotic models including Rossler, Julia, Lorenz, and Mandelbrot functions with code examples and visualization techniques
Utilizing MATLAB mathematical software for numerical computation of six significant chaotic models including the Lorenz system, while simulating unique properties of various chaotic systems such as chaotic attractors, period-doubling bifurcations, sensitivity to initial conditions, phase portraits, and bifurcation diagrams. Through observation and analysis of these characteristics, we deepen our understanding of chaotic phenomena. Implementation involves MATLAB's ODE solvers (ode45/ode15s) for system integration and specialized plotting functions for visualization.
This documentation presents Simulink-based simulations of Duffing and Lorenz chaotic systems, followed by time-delayed feedback control and synchronization control implementations for the Lorenz system. Additionally, it includes a Simulink-based sliding mode control implementation that is both convenient to setup and demonstrates effective performance.
Lorenz Time Series Dataset for Analyzing Dynamical Systems through Phase Space Reconstruction Techniques
MATLAB implementation and visualization of various chaotic systems including Rossler attractor, Lorenz system, Julia set, and Mandelbrot set
Implementation and Analysis of Four Classical Chaotic Systems with Code-Level Details