Adaptive mesh refinement techniques are well established and widely used for space discretizations. In contrast, local time stepping is much less used, and the corresponding techniques are less mature, needing delicate synchronization steps, which involve interpolation, extrapolation or projection. These operations can have adverse effects on the stability, and can also destroy important geomet...

Using measurements of Sea Surface Salinity and Sea Surface Temperature in the Western Tropical Atlantic Ocean, from 2003 to 2007 and 2009, we compare two approaches for estimating Sea Surface Salinity : Multiple Non-linear Regression and Multi Layer Perceptron. In the first experiment, we use 18,300 in situ data points to establish the two models, and 503 points for testing their extrapolation....

We present the theory and numerical results for interferometrically interpolating and extrapolating ocean bottom seismic (OBS) and surface seismic profile (SSP) data. For the interpolation of OBS data we use the combination of a natural Green’s function (i.e. OBS shot gather) and a model-based Green’s function for the water-layer model. Results show that the aliased OBS data with 80 meter geoph...

The ongoing research in Distributed Video Coding (DVC) for low complexity encoding is trying to bridge the substantial performance gap to well known state-of-the-art coders. We introduce our true motion based extrapolation scheme and compare its performance to other state of the art systems in the field of DVC. The results of the extrapolation based approach display nearly the same performance ...

The barycentric interpolation formula defines a stable algorithm for evaluation at points in [−1, 1] of polynomial interpolants through data on Chebyshev grids. Here it is shown that for evaluation at points in the complex plane outside [−1, 1], the algorithm becomes unstable and should be replaced by the alternative modified Lagrange or “first barycentric” formula dating to Jacobi in 1825. Thi...

This paper introduces a new computational operation that provides support for creative designing by adaptively exploring design state spaces. This modification is based on the re-interpretation of the crossover operation of genetic algorithms as an interpolation and its generalization to extrapolation. Examples of the results of the application of the process are presented.

We present the theory and numerical results for interferometrically interpolating and extrapolating ocean bottom seismic (OBS) data. For the interpolation of OBS data we use the combination of a natural Green’s function (i.e. OBS shot gather) and a model-based Green’s function for the water-layer model. Synthetic and field data results show that the aliased OBS data with large receiver interval...

Let f1, . . . , fL be analytic functions and ζ1, . . . , ζL be points where the functions are defined. Sharp upper bounds are known for the absolute value of the determinant of the L× L matrix ( fλ(ζμ) )

This paper serves to compare existing models of function learning (EXAM & POLE) on a complex interpolation task. Previous comparisons of the models have focused primarily on extrapolation behaviors. Participants’ mean responses suggested a simple linear interpolation from nearby points of reference. Both models were able to predict a similar response. Although POLE served as a better predictor ...