Explore MATLAB source code curated for "代码" with clean implementations, documentation, and examples.
This implementation features code integrating Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) for enhanced Support Vector Machine (SVM) performance, providing an excellent machine learning solution with comprehensive optimization capabilities.
This code repository implements genetic algorithm optimization examples from Chapter 4, Example 4-5 of "Mastering MATLAB Intelligent Algorithms" - Each function accepts vector inputs for computational efficiency and can be adapted for various optimization scenarios.
A basic MATLAB face recognition implementation featuring a personal image database and fundamental image processing techniques
This particle filter implementation provides robust moving object tracking, personally tested with excellent performance. The code includes human motion video examples - simply run the MAIN file for immediate testing with customizable parameters. Ready for download and implementation.
Code implementation for multi-objective optimization using genetic algorithms with detailed tutorial explanations. For high-resolution tutorials beyond file size limitations, please contact the author for additional materials.
Interactive Multiple Model Algorithm Kalman Filter simulation code, featuring implementation with two distinct models and dynamic switching capabilities
Code implementation for simulating Rayleigh fading and Doppler spread in shortwave channels, featuring performance comparison across different modulation schemes including Frequency Shift Keying (FSK), Phase Shift Keying (PSK), and Amplitude Shift Keying (ASK)
Code implementation of adaptive image threshold segmentation with maximum class variance method (Otsu's method) in MATLAB
Self-developed MIMO maximum likelihood algorithm code with implementation insights - for reference and technical discussion
Sub-pixel corner localization function code implementation, taking coarse pixel-level corner coordinates as input parameters and outputting precise sub-pixel level corner coordinates. This algorithm typically involves interpolation methods and gradient-based optimization techniques.