The explicit implicit domain decomposition methods are a non iterative types of methods for non overlapping domain decomposition. In comparison with the classical Schwarz algorithm for parabolic problem the former methods are computationally and communicationally more efficient for each time step but due to the use of the explicit step for the interface prediction the methods suffer from the ac...

High-resolution methods of direction-of-arrival (DOA) estimation have been a topic of great importance in recent years for their wide-spread applications in radar, sonar, and mobile communication [7, 8]. Recently, most multiple source detection techniques are based on the eigenstructure decomposition of the covariance matrix. Among them, MUltiple SIgnal Classification (MUSIC) method [13] and Es...

Domain decomposition based on spatial locality is a classical dataparallel problem whose solution may improve by orders of magnitude when implemented on a GPU. Among the data structures involved in domain decomposition, uniform grids are widely used to speed up simulations in a number of fields, including computational physics and graphics. In this work, we present two commonly used approaches ...

This paper is devoted to the fast solution of interface concentrated finite element equations. The interface concentrated finite element schemes are constructed on the basis of a non-overlapping domain decomposition where a conforming boundary concentrated finite element approximation is used in every subdo-main. Similar to data-sparse boundary element domain decomposition methods the total num...

Frequency-transformed EEG resting data has been widely used to describe normal and abnormal brain functional states as function of the spectral power in different frequency bands. This has yielded a series of clinically relevant findings. However, by transforming the EEG into the frequency domain, the initially excellent time resolution of time-domain EEG is lost. The topographic time-frequency...