This paper presents an efficient method for extracting a multi-model interpolation function from a nonlinear system. The multi-model interpolation function consists of couple simplified time-varying models in neural-network structure to dynamically approximate the nature of the physical phenomena to be interpolated and extrapolated. The purpose of using the multi-model interpolation function is...

Many medical images suffer from the partial volume effect where a boundary between two structures of interest falls in the midst of a voxel giving a signal value that is a mixture of the two. We propose a method to restore the ideal boundary by splitting a voxel into subvoxels and reapportioning the signal into the subvoxels. Each voxel is divided by nearest neighbor interpolation. The gray lev...

We introduce a dispersionless integrable system which interpolates between the dispersionless Kadomtsev–Petviashvili equation and the hyper–CR equation. The interpolating system arises as a symmetry reduction of the anti–self–dual Einstein equations in (2, 2) signature by a conformal Killing vector whose self–dual derivative is null. It also arises as a special case of the Manakov–Santini integ...

We introduce a dispersionless integrable system which interpolates between the dispersionless Kadomtsev–Petviashvili equation and the hyper–CR equation. The interpolating system arises as a symmetry reduction of the anti–self–dual Einstein equations in (2, 2) signature by a conformal Killing vector whose self–dual derivative is null. It also arises as a special case of the Manakov–Santini integ...

Numerical time-step limitations associated with the explicit treatment of advection-dominated problems in computational uid dynamics are often relaxed by employing Eulerian-Lagrangian methods. These are also known as semi-Lagrangian methods in the atmospheric sciences. Such methods involve backward time integration of a characteristic equation to nd the departure point of a uid particle arrivin...

Interpolation techniques for spatial data have been applied frequently in various fields of geosciences. Although most conventional interpolation methods assume that it is sufficient to use firstand second-order statistics to characterize random fields, researchers have now realized that these methods cannot always provide reliable interpolation results, since geological and environmental pheno...

This paper describes a novel theoretical approach for the improvement of the bivariate linear interpolation function. The fundamental premise of this theory consists of quantifying the effect of the interpolation function on an image’s pixel by the product of the value of the pixel intensity times the sum of non-null second order derivatives of the function. The product is called intensity-curv...