Professional MATLAB source code with comprehensive documentation and examples
A comprehensive MATLAB toolbox designed for implementing and analyzing Pulse Coupled Neural Network algorithms, featuring ready-to-use functions for neural simulation, parameter configuration, and result visualization to facilitate research and appli
EEMD Empirical Mode Dedition with Artificial Neural Network Classification for Advanced Signal Processing
Extended Kalman Filter Algorithm for Nonlinear System State Estimation
Comprehensive MATLAB source code for machine learning, featuring multi-class SVM algorithms, pattern recognition systems, feature selection methods, and various regression techniques with practical implementation examples.
The ANN-based neural network prediction method enables accurate plotting of curves comparing predicted values versus actual values, along with error analysis curves for comprehensive performance evaluation
MATLAB implementation for face detection combining high wavelet feature extraction with neural network classification
This implementation demonstrates how Particle Swarm Optimization (PSO) enhances Least Squares Support Vector Machine (LSSVM) classification accuracy by automatically tuning hyperparameters like regularization and kernel parameters, achieving superior
Comparative analysis of simulation results between adaptive genetic algorithm-optimized RBF neural networks and particle swarm optimization-optimized RBF neural networks, featuring directly executable MATLAB code implementations.
MATLAB implementation of a BP neural network designed for handwritten digit recognition, highly practical and ready to execute with immediate results demonstration
A practical application example of Generalized Regression Neural Network (GRNN) suitable for learning and implementation purposes, featuring code structure insights and algorithm explanations.
This example demonstrates nonlinear function fitting by applying optimal individuals obtained from genetic algorithms to BP neural networks. The implementation involves MATLAB programming for genetic algorithm optimization of BP neural network models
Implementation of DC motor position control through genetic algorithm-optimized PID controller parameters, including proportional, integral, and derivative gain tuning strategies.
This program provides a standard Particle Swarm Optimization (PSO) implementation in MATLAB, accompanied by a PDF document explaining the PSO algorithm and its code implementation details.
MATLAB-based artificial immune algorithm implementation with applications in fault diagnosis systems, featuring immune-inspired optimization mechanisms and pattern recognition capabilities.
Implements neural network-based intelligent recognition compilation, rapidly identifying various animals based on their distinct features through deep learning algorithms and image processing techniques
Implementation of Fuzzy C-Means Clustering Algorithm for image classification, digital image processing, multi-category segmentation, and SAR image classification with enhanced feature extraction methods.
Basic Ant Colony Clustering Algorithm with enhanced convergence capabilities, featuring comprehensive code annotations to address previous non-convergence issues.
Utilizing genetic algorithms to optimize fuzzy control systems, including implementation approaches for parameter tuning and performance enhancement
MATLAB implementation of a three-layer BP artificial neural network to solve the XOR problem, featuring adjustable network architecture with configurable hidden layer neurons and activation functions
MATLAB implementation of Particle Swarm Optimization algorithm with "MAIN" as the primary program file containing core algorithm components