Principles of Hidden Markov Models with MATLAB Implementation
Comprehensive explanation of Hidden Markov Model principles accompanied by MATLAB code implementation, including executable demos to demonstrate HMM workflow and practical applications
ASIFT Image Feature Extraction with Source Code Implementation
Complete ASIFT image feature extraction source code package including sample test images and demonstration program
SIFT Image Matching Algorithm
A classic scale-invariant feature transform (SIFT) image feature matching algorithm implementation. This package includes detailed explanations and demonstration code adapted from international sources, featuring comprehensive line-by-line comments for easy code modification and extension.
Demo for Quick Image Blur Enhancement Implementation
A collection of MATLAB source code demos for rapid image blur enhancement, all thoroughly tested and verified to work correctly.
Wavelet Soft-Threshold Denoising Processing Method
Wavelet soft-threshold denoising processing method with program demonstration and implementation details
Wavelet Transform Toolbox Developed by International Researchers
A MATLAB-based wavelet analysis toolbox created by international developers, featuring comprehensive documentation and practical demonstration scripts that provide high reference value for signal processing applications.
Dynamic Object Tracking in Videos Using MATLAB
MATLAB implementation of dynamic object tracking in videos with effective results, previously tested with included demo programs featuring algorithms like optical flow and Kalman filtering.
Detailed Implementation of GMDH Neural Network
Comprehensive GMDH neural network program with demo as the main executable, featuring modular architecture and step-by-step implementation guide
A Demo of Cyclic Spectral Density in Signal Processing
This is a demonstration of cyclic spectral density in signal processing, which some literature refers to as the composite slices of cyclostationary signals.
CNN Convolutional Neural Network for Handwritten Digit Recognition
This MATLAB implementation of a CNN convolutional neural network achieves approximately 50% accuracy in handwritten digit recognition, with cnet_tool.m serving as the main demonstration file showcasing dataset loading, model training, and performance evaluation processes.