Explore MATLAB source code curated for "信息熵" with clean implementations, documentation, and examples.
Implementation guide for computing information entropy and mutual information between discrete time series variables with probability distribution calculations and algorithmic steps
Implementation of information entropy and mutual information calculations for two images using MATLAB with code examples and algorithm explanations.
The information entropy-based immune algorithm is a modified immune algorithm with a straightforward methodology that delivers strong performance for specific problem domains, featuring entropy calculation functions and enhanced antibody diversity management.
An enhanced genetic algorithm incorporating information entropy principles and population concentration-based update operators for improved diversity and performance.
MATLAB implementation for calculating standard deviation and information entropy metrics to evaluate image fusion quality, featuring comprehensive code descriptions and algorithm explanations.
This is a comprehensive collection of 13 image fusion performance metrics gathered from online sources, including Average Gradient, Edge Intensity, Information Entropy, Gray Mean Value, Standard Deviation (Mean Square Error MSE), Root Mean Square Error, Peak Signal-to-Noise Ratio (PSNR), Spatial Frequency (SF), Image Definition, Mutual Information (MI), Structural Similarity (SSIM), Cross Entropy, and Relative Standard Deviation. Let's share and discuss implementation approaches together!
MATLAB implementation for attribute reduction featuring information entropy and fuzzy information entropy approaches; these algorithms handle both discrete and numerical variables simultaneously without requiring discretization preprocessing.
Information Entropy: The fundamental role of information is to eliminate uncertainty about events. When multiple particles combine, they encode valuable data in their ambiguous forms, which in game theory manifests as information chaos—a phenomenon where participants face unpredictable conditions due to limited knowledge of opponents’ strategies.
Compute image characteristics including average gradient, edge strength, information entropy, and variance for both single-band and multi-band images, with implementation insights using computer vision algorithms.
Step-by-step guide to compute wavelet packet information entropy with detailed technical explanations and MATLAB code implementation approaches