Explore MATLAB source code curated for "程序" with clean implementations, documentation, and examples.
This resource presents HMM algorithm implementations using MATLAB's HMM toolbox, demonstrating practical code examples and providing helpful tools for pattern recognition and time series analysis applications.
A practical MATLAB program for computing the gray-level co-occurrence matrix of images, featuring optimized code structure and texture analysis capabilities
A comprehensive collection of commonly used Particle Swarm Optimization algorithms, including basic PSO, linearly varying PSO, constriction factor PSO, random weight PSO, and more - designed to facilitate learning and implementation
A comprehensive PSO program package consisting of three core files: DeJong.m (fitness function), get_psoOptions.m (configuration settings), and pso.m (main algorithm). Simply copy these files to your MATLAB work directory for immediate execution. Customize parameters through get_psoOptions.m and modify the objective function in DeJong.m to adapt the algorithm to specific optimization problems.
This MATLAB program implements Turbo code, a powerful channel coding and error correction technique that ensures reliable data transmission quality through iterative decoding algorithms.
A robust GPS signal acquisition and tracking program that's ready to run out-of-the-box. Features extensively commented code ideal for beginners learning GPS signal processing algorithms, including correlation-based acquisition and phase-locked loop tracking implementations.
Uploaded several programs for maneuvering target tracking based on the current statistical model, including subroutines, reference literature, and particle filter-based target tracking programs with detailed algorithm implementations and MATLAB function descriptions
Standard BP neural network algorithm implementation featuring momentum BP algorithm and PSO-optimized neural network using TRAINGDX training method. The code includes neural network training routines with gradient descent optimization techniques.
Five comprehensive PCA-based fault diagnosis routines for industrial systems, including Kernel PCA (KPCA) implementation. These well-documented MATLAB routines feature detailed code annotations, algorithm explanations, and practical examples for industrial fault detection using principal component analysis methodologies.
A comprehensive MATLAB program implementing the complete Hilbert-Huang Transform methodology for time series analysis.