Professional MATLAB source code with comprehensive documentation and examples
Support Vector Machine automatically extracts fuzzy rules with reliability verified through simulation results, demonstrating robust pattern recognition capabilities through margin maximization and kernel functions.
Source code implementation for training Adaboost classifiers - essential component for high-performance face detection systems with algorithmic enhancements and implementation details.
Implementation of a BP neural network that trains on multiple iris dataset samples and tests classification performance, with detailed code explanations for network architecture, training process, and prediction algorithms
Source code implementation of ID3 and C4.5 decision tree algorithms for data mining applications, featuring entropy calculations and information gain optimization.
MATLAB source code implementation for optimizing RBF radial basis function neural networks using genetic algorithms, featuring complete algorithm workflow and parameter configuration.
Source code implementations for feedforward neural networks including practical examples of sensor networks, BP networks, and radial basis function (RBF) networks with detailed algorithm explanations
This is a Particle Swarm Optimization (PSO) program designed for system model identification, primarily used when system parameters are unknown, making it particularly convenient for such scenarios.
Quantum Particle Swarm Optimization Implementation in MATLAB - Leveraging quantum mechanics principles to enhance traditional PSO efficiency, with experimental results demonstrating significant improvements in computational accuracy and performance
Source code implementation using Adaptive Neuro-Fuzzy Inference System (ANFIS) for chaotic time series prediction with enhanced algorithm explanations
Implementation of ICA Algorithm for Face Recognition Using MATLAB
Code examples demonstrating various applications of feedforward neural networks, implemented using MATLAB source code with detailed algorithmic explanations
An excellently written implementation of the artificial fish swarm algorithm, ideal for beginners with code examples and detailed explanations.
A fuzzy clustering program with comprehensive documentation detailing each step of the fuzzy clustering algorithm implementation.
A prediction algorithm based on wavelet neural networks, implemented and validated in MATLAB with high computational efficiency.
Freight Volume Forecasting with Generalized Regression Neural Network (GRNN) - A neural network-based data prediction model for freight volume analysis
Implementation of fundamental Bayesian decision theory algorithms in MATLAB for pattern recognition systems, providing core probabilistic classification functionality
A simple simulation of Parzen window classification in pattern recognition, where female.txt and male.txt serve as training samples and test.txt contains test samples. This implementation demonstrates excellent classification performance and provides
A MATLAB-based implementation approach for a new immune algorithm, featuring simple and practical code with zero redundancy. The implementation demonstrates efficient optimization capabilities through streamlined algorithmic structure.
Implementing neural networks with MATLAB using the newff() function to create a two-layer feedforward network. The network accepts inputs in the range [-1, 1], with the first layer containing 10 neurons using tansig activation functions. This impleme
C-means clustering algorithm source code that trains on input data and classifies categories, enabling generation of data clustering diagrams with centroid initialization and iterative optimization.