Explore MATLAB source code curated for "Matlab实现" with clean implementations, documentation, and examples.
Gray-Level Co-occurrence Matrix (GLCM) and Gray-Level Gradient Co-occurrence Matrix (GLGCM) extraction methods are significant texture feature extraction techniques implemented using MATLAB for image processing applications.
Application Context: In statistical computing, the Expectation-Maximization (EM) algorithm is used to find maximum likelihood or maximum a posteriori estimates of parameters in probabilistic models that depend on unobserved latent variables. The EM algorithm is frequently applied in machine learning and computer vision for data clustering tasks. Key Technology: The EM algorithm iterates through two alternating steps: - E-step (Expectation): Computes the expected value of the log-likelihood function using current estimates of hidden variables - M-step (Maximization): Finds parameters that maximize the expected log-likelihood computed in the E-step Parameters estimated in the M-step are reused in the next E-step, creating an iterative convergence process.
MATLAB Implementation of Receiver-Side Maximum Ratio Combining with Performance Comparison Analysis
MATLAB code implementation demonstrating how to generate both two-dimensional and three-dimensional Hilbert-Huang Transform spectral plots, complete with signal processing workflow and visualization techniques.
Feature selection methods with MATLAB implementations including l-add r-remove algorithm, Sequential Floating Forward Selection (SFFS), sequential backward selection, and sequential forward selection with code implementation details
MATLAB implementation of the Snake Model, commonly known as the Active Contour Model, including the original research paper and comprehensive code documentation.
MATLAB implementation of maximum negentropy-based Independent Component Analysis with orthogonalization processing, capable of separating all independent components simultaneously under noise-free conditions
MATLAB implementation of a classic image processing approach combining Gaussian Mixture Model background modeling and skin color detection algorithms for facial detection applications
MATLAB-based 7-parameter conversion utility with flexible implementation and GUI enhancement possibilities
Implementing Hough transform-based line detection in MATLAB with corrected code errors and enhanced functionality, ready for immediate execution with improved performance.