Explore MATLAB source code curated for "学习" with clean implementations, documentation, and examples.
This toolkit implements multi-resolution analysis based image fusion algorithms, including region-based fusion approaches. The corresponding programs are supported by technical papers, serving as essential learning resources for image fusion studies with practical code demonstrations.
This project implements a QAM communication system simulation using MATLAB, providing valuable insights for academic learning and professional applications in digital communications.
SVM applied to face recognition with satisfactory performance! MATLAB implementation for educational purposes with practical coding examples.
A classic MATLAB implementation of the SIFT algorithm for image registration, ideal for beginners to study computer vision fundamentals and feature extraction techniques.
MATLAB source code featuring: 1. Complete implementation of BP neural network and ELM training/learning processes 2. Data extraction code for eye open/close state detection from images 3. Comprehensive image dataset for eye state classification validation
This algorithm presents an improved version of the K-SVD algorithm, designed specifically for sparse dictionary learning. It effectively reduces computational complexity and accelerates dictionary update speed compared to traditional methods. The implementation typically involves optimized sparse coding steps and efficient singular value decomposition (SVD) operations.
MATLAB-based image processing algorithms with 6 distinct program implementations, providing valuable learning resources for both beginners and experienced practitioners in digital image processing.
A comprehensive guide to RBF neural network algorithms, providing substantial assistance and guidance for learners studying RBF networks with practical code implementation details.
A MATLAB-based implementation example of RBF neural network modeling, featuring practical code demonstrations and algorithm explanations to facilitate effective learning of RBF modeling techniques
This project provides MATLAB-based implementations of OFDM transmission and reception systems, featuring detailed code explanations, algorithm implementations, and practical programming techniques for educational reference.