Support Vector Regression (SVR) Implementation Guide
A practical application of Support Vector Regression machine! Perfect for beginners learning prediction modeling with clear code examples and algorithm explanations.
Professional MATLAB source code with comprehensive documentation and examples
A practical application of Support Vector Regression machine! Perfect for beginners learning prediction modeling with clear code examples and algorithm explanations.
MATLAB-based Backpropagation Neural Network programming with detailed algorithm explanation and practical applications
A MATLAB implementation of pedestrian detection using HOG (Histogram of Oriented Gradients) features combined with AdaBoost classifier, including extensive training and testing image datasets required for program execution.
This assignment provides a comprehensive guide for those starting with Support Vector Machines, covering fundamental concepts, implementation approaches, and practical examples using scikit-learn.
Adaptive Genetic Algorithm - Basic Version with Customizable Objective Function Implementation
Photovoltaic grid-connected simulation module implementing MPPT (Maximum Power Point Tracking) using PSO (Perturb and Observe) algorithm with code-level optimization features
This resource provides the complete source code for a standard wavelet neural network implementation, featuring significant academic value with detailed algorithm explanations and MATLAB/Python-compatible code structure.
This MATLAB program implements digit recognition through a backpropagation neural network, featuring complete training workflow including data preprocessing, network architecture design, and iterative optimization with performance monitoring.
PSO Particle Swarm Optimization algorithm demonstration program featuring a graphical user interface with real-time visualization of particle movement and convergence dynamics.
Implementation of Wavelet Neural Networks (WNN) for Pattern Recognition Processing in MATLAB
SOM neural networks perform feature extraction and pattern classification, particularly effective for high-dimensional feature spaces. Implementation typically involves competitive learning algorithms, neighborhood functions, and weight adaptation me
Detailed explanation of the establishment, model training, testing, and normalization processes for three neural network architectures, with performance evaluation and comparative analysis of different network performances, including result compariso
A density-based clustering algorithm for 2D data that takes (x,y) coordinate arrays, search radius Eps, and density threshold Minpts as inputs. The implementation outputs clusters in array format where each row represents a cluster containing the ori
SVM multiclass classifier implementation featuring multi-class classification capabilities enhanced with Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) for parameter optimization
This MATLAB genetic algorithm code provides a well-structured implementation with customizable parameters including selection, crossover, and mutation operations - simply download, extract, and integrate into your projects
This document contains a research paper on fast learning algorithms for BP wavelet neural networks, along with two wavelet algorithm implementations developed using MATLAB, including simulation results and performance analysis.
ICA-based feature extraction and recognition system with video processing components including binarization source code, frame-by-frame processing algorithms, and object tracking implementation. Features a master's thesis project on video gesture tra
MATLAB code for fuzzy neural network implementation with practical examples and algorithm explanations
MATLAB program for Immune Genetic Algorithm featuring six core modules: antigen recognition, initial antibody generation, fitness evaluation, memory cell differentiation, antibody promotion and suppression, and antibody reproduction (crossover and mu
Contains introductory materials for neural networks with progressive advancement, along with various neural network toolboxes featuring implementation examples.