Explore MATLAB source code curated for "熵" with clean implementations, documentation, and examples.
Normalization of the co-occurrence matrix using the gray-level co-occurrence matrix and calculation of four texture parameters: energy, entropy, moment of inertia, and correlation, with code-related implementation details.
Techniques for image degradation and computation of four key texture parameters (energy, entropy, inertia moment, correlation) from co-occurrence matrices with implementation considerations
Includes computing the co-occurrence matrix, normalizing the co-occurrence matrix, calculating four texture parameters (energy, entropy, inertia moment, correlation) from the co-occurrence matrix, and deriving the mean and standard deviation of energy, entropy, inertia moment, and correlation as the final 8-dimensional texture feature vector
MATLAB-based texture analysis program capable of computing key statistical features including entropy, contrast, mean, and variance with algorithm explanations
Texture feature extraction based on Gray-Level Co-occurrence Matrix (GLCM). Key feature parameters include: entropy, energy, contrast, and homogeneity.
Voice Activity Detection program implementing multi-band analysis, entropy measurements, spectral entropy, and Teager energy computation for robust speech signal processing applications
General computational methods for core information theory concepts including entropy, joint entropy, conditional entropy, and mutual information with code implementation insights
General computational approaches for key information theory metrics including entropy, joint entropy, conditional entropy, and average mutual information with code implementation considerations
Comprehensive calculation methods for core information theory metrics including entropy, joint entropy, conditional entropy, and mutual information with code implementation considerations