Principles of Blind Source Separation Using Independent Component Analysis
Introduction to the principles of blind source separation using Independent Component Analysis with practical code examples
Explore MATLAB source code curated for "例程" with clean implementations, documentation, and examples.
Introduction to the principles of blind source separation using Independent Component Analysis with practical code examples
A double hidden layer backpropagation neural network routine designed for educational purposes, featuring clear algorithm explanations and practical code implementation details.
A collection of practical code routines extracted from wavelet analysis theory, featuring algorithm explanations and key function descriptions for technical reference and implementation guidance.
A practically tested implementation of dynamic fuzzy neural networks with functional codebase and documented performance results.
Image Processing: Calculating Peak Signal-to-Noise Ratio (PSNR) in MATLAB with validated working examples
MATLAB routine featuring simple and easy-to-understand k-medoids clustering algorithm source code with detailed implementation insights
Implementation of clustering and classification routines using SVM algorithm. Includes experimental datasets, execution results, and a classic reference paper titled "A New Fuzzy Cover Approach to Clustering". Code enhancements demonstrate feature scaling, kernel selection, and hyperparameter optimization techniques.
A comprehensive MATLAB-based EEG processing library featuring extensive example routines with clear explanations, essential for medical image and graphics processing applications
This set of programs provides a wavelet transform-based speech denoising routine, where each program's specific functionality can be found in the source code.
This routine demonstrates signal processing using wavelet analysis, providing valuable learning material for understanding wavelet applications with practical code implementation examples.