Bitcoin’s power law accounts for 98.70% of price variance, confirmed as the dominant eigenmode of its system. Dynamic Mode Decomposition identified a 1,530-day oscillation, matching Bitcoin’s ...
Principal component analysis (PCA) is a classical machine learning technique. The goal of PCA is to transform a dataset into one with fewer columns. This is called dimensionality reduction. The ...
Abstract: An analytic parahermitian matrix admits in almost all cases an eigenvalue decomposition (EVD) with analytic eigenvalues and eigenvectors. We have previously defined a discrete Fourier ...
Modularity, a widely recognized principle of living systems, has been observed in many aspects of biological organization (Wagner et al., 2007). In the eukaryotic genome, the highest level of physical ...
JED is a program for performing Essential Dynamics of protein trajectories written in Java. JED is a powerful tool for examining the dynamics of proteins from trajectories derived from MD or Geometric ...
Principal component transformation is a standard technique for multi-dimensional data analysis. The purpose of the present article is to elucidate the procedure for interpreting PC images. The ...
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