Professional MATLAB source code with comprehensive documentation and examples
Comprehensive MATLAB implementation of Support Vector Machine (SVM) algorithm featuring practical examples, technical documentation, and detailed explanations on data classification using MATLAB's built-in functions and custom code implementations
Supplemental materials for neural network implementation with MATLAB 7 in .m format, including core algorithms and practical examples
Lin Jian's experimental work on MATLAB applications in image processing and object recognition, featuring chromosome identification and statistics, vehicle license plate localization and character recognition, and a basic experiment using BP neural n
A MATLAB-implemented quantum particle swarm optimization algorithm providing efficient multidimensional function optimization with enhanced global search capabilities to prevent local optima convergence.
MATLAB source code implementing Differential Evolution optimization for Extreme Learning Machine neural networks, featuring algorithm integration and performance enhancement techniques.
A MATLAB implementation of classic Support Vector Machine (SVM) for classification tasks, featuring identification, categorization, and parameter optimization capabilities with detailed algorithmic explanations.
Building, training, and performing fuzzy inference calculations with fuzzy neural network structures, including implementation methods and parameter optimization techniques.
A MATLAB-based genetic algorithm implementation for path planning with satisfactory performance, suitable for academic projects like graduation theses with support for result visualization through screenshots.
A neural network classifier based on Dempster-Shafer evidence theory, featuring uncertainty modeling and evidence combination mechanisms for robust pattern recognition.
This MATLAB-based resource provides executable code implementations for multiple advanced control methodologies. Each technique includes practical examples demonstrating controller design, parameter tuning procedures, and performance analysis. The co
MATLAB implementation of Mean Shift algorithm for clustering analysis and image processing applications
AdaBoost classifier MATLAB source code for training samples and implementing classification with weak learner combination algorithms
A parameter optimization program for libsvm that provides full grid search optimization specifically designed for SVR (Support Vector Regression), primarily used for SVM regression prediction with detailed implementation of parameter tuning algorithm
PID control program design using BP neural network (includes simulation graphs generated after program execution) with algorithm integration and performance visualization
Complete source code implementation for BP neural network function approximation, featuring backpropagation algorithm with gradient descent optimization for nonlinear function mapping
The DV-hop based localization methods incorporating particle swarm optimization and genetic algorithms demonstrate superior performance with enhanced precision and convergence rates.
Using Particle Swarm Optimization to optimize BP neural network weights, the trained neural network is applied to fault diagnosis for pattern recognition, achieving faster convergence compared to standard BP neural networks
Implementation of Backpropagation Neural Networks for data forecasting using MATLAB, featuring code architecture and algorithmic workflows.
Comprehensive introduction to Differential Evolution and Particle Swarm Optimization algorithms with detailed MATLAB code implementations, including key functions and parameter configurations
This SAR image segmentation approach utilizes Markov Random Field modeling with Maximum a Posteriori probability criterion for target slice segmentation, solved through clustering analysis algorithms. The implementation involves probability distribut