MATLAB Source Code for Path Planning Based on Genetic Algorithm
Genetic Algorithm Path Planning MATLAB Source Code with Grid-based Environment Modeling Method
Machine Learning Source Code for Dimensionality Reduction, Feature Selection, and Related Algorithms
Comprehensive machine learning source code authored by Zhejiang University professors Cai Deng and He Xiaofei, covering spectral regression, dimensionality reduction, feature selection, topic modeling, matrix factorization, sparse coding, hashing techniques, clustering methods, active learning, and matrix learning. This collection serves as an excellent resource for understanding algorithm implementations through practical code examples.
Fingerprint Recognition MATLAB Source Code
Fingerprint Recognition MATLAB Implementation with Complete Source Code and Algorithm Explanations
Source Code for Classification Algorithm Implementation using Support Vector Machine (SVM)
MATLAB-based source code implementing Support Vector Machine (SVM) classification algorithm with detailed technical analysis
MATLAB Source Code for Face Detection Using High Wavelet Feature Extraction and Neural Networks
MATLAB implementation for face detection combining high wavelet feature extraction with neural network classification
Expression Recognition Source Code with Direct PCA and SVM Function Calls
A facial expression recognition source code that directly implements PCA and SVM functions for efficient emotion classification.
Foreign Artificial Bee Colony Algorithm (ABC) Source Code
Source code implementation of the Artificial Bee Colony Algorithm (ABC) with detailed optimization capabilities
Wavelet Multi-Scale Grayscale Image Texture Feature Detection Source Code
Source code for grayscale image texture feature detection based on wavelet multi-scale analysis, featuring customizable wavelet parameters for algorithm optimization
Source Code for Second-Generation Lifting Wavelet Threshold Compression Algorithm
This source code implements a threshold-based compression algorithm using second-generation lifting wavelets. Key customizable parameters include decomposition levels, wavelet types, and threshold calculation formula coefficients for each level. The implementation converts low-frequency coefficients to hexadecimal format to facilitate further compression techniques like Huffman coding. The well-commented code demonstrates clear implementation logic, supports multiple wavelet families, and effectively illustrates second-generation wavelet concepts - making it particularly valuable for wavelet beginners.
SOMP Algorithm: Subspace Reconstruction in Compressed Sensing
SOMP (Subspace Orthogonal Matching Pursuit) is a subspace reconstruction algorithm in compressed sensing. This repository provides MATLAB/Python implementation code and technical paper discussing the algorithm's sparse signal recovery mechanism and iterative optimization approach.