MATLAB Implementation and Visualization of Autocorrelation and Cross-Correlation Functions
Comprehensive guide to computing and plotting autocorrelation and cross-correlation functions using MATLAB with code implementation examples
Explore MATLAB source code curated for "Matlab" with clean implementations, documentation, and examples.
Comprehensive guide to computing and plotting autocorrelation and cross-correlation functions using MATLAB with code implementation examples
MATLAB-based flight simulation experimental program for unmanned aerial vehicle mathematical models, featuring detailed implementations of flight dynamics and control algorithms.
A practical MATLAB example demonstrating 3D reconstruction through structured light techniques, including pattern projection, deformation analysis, and 3D model generation.
This study explores the practical applications of MATLAB in nonlinear curve fitting, which proves highly beneficial for computational modeling. As a learner in this field, I found substantial value in understanding these techniques. Key MATLAB functions like `lsqcurvefit` and `fitnlm` implement optimization algorithms for parameter estimation, while graphical tools like the Curve Fitting Toolbox simplify iterative refinement processes.
MATLAB simulation program for PM ocean wave spectra analysis under varying wind speed conditions
This MATLAB source code calculates and graphically visualizes the workspace of parallel robots, implementing kinematic constraints and spatial boundary detection algorithms.
This program enables robot formation simulation in MATLAB, featuring sensor modules, communication modules, controller modules, and environmental perception modules. The modular architecture allows easy modification and implementation through parameter adjustments in respective functional blocks. MATLAB is a high-performance numerical computation and visualization software developed by MathWorks, renowned as an internationally acclaimed scientific computing environment that integrates matrix operations, signal processing, and graphical display capabilities.
MATLAB implementation of traffic flow cellular automaton featuring: * Car-following functionality (implemented using velocity adjustment algorithms based on headway distance) * Lane-changing functionality (using decision matrices with safety/gap acceptance criteria) * Cellular space definition (configurable grid parameters via matrix initialization) * Vehicle definition (object-oriented properties for type, dimensions, and kinematic parameters) * Driver characteristic definition (behavioral parameters including reaction time and decision thresholds) * Departure density definition (Poisson distribution or time-based vehicle generation) * Signal timing definition (configurable traffic light cycles using state machines) * Lane-changing ratio definition (probabilistic rule-based parameter controls)
Experiment Objective: Implement the branch and bound method in MATLAB to solve integer linear programming problems. Experiment Content: Apply the branch and bound algorithm to find the optimal solution for a given linear integer programming problem, including detailed implementation steps and code structure explanation.
Multiple MATLAB programs for interferometer direction finding with cross-compatibility features. Includes FFT-based implementations and five core algorithms with essential computational modules for signal processing and direction of arrival estimation.