Latin Hypercube Sampling Method for Correlated Wind Speed Sequences
An example implementation of Latin Hypercube Sampling for correlated wind speed sequences, featuring Cholesky decomposition and ranking correlation preservation techniques
Extracting Five Texture Features Using Gray Level Co-occurrence Matrix
Extract five key texture features using Gray Level Co-occurrence Matrix (GLCM): entropy, homogeneity, correlation, energy, and contrast
Comparative Study of M-Sequence Correlation with Algorithm Implementation Insights
Investigation of m-sequence correlation properties, generation methodologies including code implementation approaches, and applications of m-sequence autocorrelation functions in various technical domains
Conventional Wavelet Threshold Denoising Methods
Conventional wavelet threshold denoising methods operate under the assumption that wavelet coefficients are independent, neglecting their correlations across adjacent scales, which results in an inherent trade-off between noise removal and preservation of useful high-frequency information.
Neighborhood Correlation-Based Redundant Second Generation Wavelet Denoising Method
By introducing the noise reduction concept of wavelet adjacent coefficient correlation into redundant second generation wavelets, this paper proposes a denoising method that overcomes the limitation of traditional threshold denoising methods which fail to consider correlations between wavelet coefficients. The implementation involves correlation analysis within wavelet coefficient neighborhoods and adaptive thresholding based on local statistical properties.