Web18 de dez. de 2024 · Higher-order spectral (HOS) analysis is a nonlinear method that helps to obtain characterization changes in signals, which can be used as features for the automated classification. HOS can be used to capture nonlinear dynamic characteristic changes in biomedical signals. Web10 de abr. de 2024 · Kinds of higher-order matrix spectral problems were introduced and their associated integrable Hamiltonian hierarchies were generated through the zero-curvature formulation. A crucial step was to formulate a Laurent series solution to the corresponding stationary zero-curvature equations.
(PDF) Higher-order Spectral Method for Regular and Irregular …
Web22 de nov. de 2016 · A wide range of methods utilising translation process theory have been developed [11,12,13]. More recently, a class of methods has been developed that theoretically extends the SRM to... Web15 de mar. de 2024 · While the standard spectral clustering is often not effective for geometric graphs, we present an effective generalization, which we call higher-order spectral clustering. It resembles in concept the classical spectral clustering method but uses for partitioning the eigenvector associated with a higher-order eigenvalue. cliff adrian mi
Accuracy of High Order and Spectral Methods for Hyperbolic …
Web18 de dez. de 2024 · Thereafter, with a higher-order spectral method (HOSM) as the SWD API solution, irregular waves with different wave heights and water depths relevant for e.g. aquaculture and offshore structures are simulated. Differences between the HPC and HOSM solutions in and near steep crests are investigated. WebA high-order method with fast implementation that allows to compute on a finer mesh or using a higher polynomial degree with the same amount of computational costs is superior (although it is... Web1 de nov. de 2014 · Quantitative spectral comparison by weighted spectral difference for protein higher order structure confirmation Previously, different approaches of spectral comparison were evaluated, and the spectral difference (SD) method was shown to be valuable for its linearity with spectral changes and its independence on data … cliff adventure 640