Professional MATLAB source code with comprehensive documentation and examples
MATLAB program implementation of ant colony optimization algorithm for solving continuous function optimization problems, featuring parameter adjustment strategies and performance enhancement techniques.
This program implements genetic algorithm optimization for BP neural networks, featuring excellent performance and valuable learning content
Implementation of a classical pedestrian detection algorithm using HOG features and SVM classification, fully debugged and ready for deployment.
Implementation of time series forecasting combining Support Vector Machine Regression with Phase Space Reconstruction methodology
Clustering optimization algorithm based on the artificial bee colony algorithm with implementation insights
A practical implementation of multiscale image edge detection based on wavelet transform modulus maxima, serving as a modular component in my pattern recognition system with clear algorithmic structure and MATLAB-compatible implementation approach
Numerous PSO optimization algorithms including BPSO (Binary Particle Swarm Optimization), HybridPSO (Hybrid Particle Swarm Optimization), QPSO (Quantum Particle Swarm Optimization), SPSO (Improved Particle Swarm Optimization), and more.
MATLAB Support Vector Machine prediction with complete dataset, case analysis, and thoroughly debugged source code (original author's program personally verified). Requires libsvm toolbox installation prior to execution. Case study focuses on short-t
Multi-frame image super-resolution reconstruction achieved through machine learning, demonstrating excellent performance with robust algorithm implementation.
Implementation of a hybrid approach combining Ant Colony Optimization (ACO) algorithm with Backpropagation (BP) Neural Network, featuring enhanced optimization through pheromone-based path selection and gradient descent weight adjustments.
An operational ant colony optimization algorithm for path finding applications, particularly suitable for robot path optimization with detailed implementation approaches
Implementing Function Optimization with Genetic Algorithm in MATLAB Code
Mean shift segmentation algorithm with MATLAB code examples featuring clustering analysis and parameter optimization techniques
This SVM toolbox extends LIBSVM with three parameter search methods and integrated plotting functions for enhanced model visualization and optimization
The following code implements a recognition application using neural network technology. The probabilistic neural network model aids in pattern identification by incorporating intelligent learning mechanisms through neural network architectures.
Neural network algorithm is a powerful computational method, and this example demonstrates its application in radar echo signal image reconstruction through neural network-based signal processing.
This project demonstrates the MATLAB implementation of Support Vector Machines (SVM), organized into five distinct folders representing different SVM variants with corresponding code examples and algorithm implementations.
Implementation of FCM clustering algorithm in MATLAB, along with other clustering algorithms including K-means and hierarchical clustering, featuring detailed code descriptions and practical applications.
MATLAB-based simulation program implementing a dual-input dual-output PID neural network with detailed code implementation
Wind power forecasting based on PSO-optimized SVM algorithm, employing Particle Swarm Optimization to enhance Support Vector Machine parameters for improved prediction performance.