Cellular Neuronal Network Grids - a scientific solution with Grid computing
Original Publication Date: 2004-Jul-15
Included in the Prior Art Database: 2004-Jul-15
A catenation between the universal paradigm of Cellular Neural Networks (CNN) and the innovative approach of grid computing in the on-demand area is given. CNN are a massive parallel solutions for solving non-linear problems, modelling complex phenomena in medicine, physics and data analysis as well as powerful image processing and recognition systems. They usually are simulated on local computer systems or build as dedicated VLSI-implementations. However, the research of complex CNN structures and settings require massive computing power and thus can benefit from multi-system open architectures which can be provided by the grid approach. Propositions of two different realizations with grid architecture in mind are given by introducing an algorithm of implementing such methods in a CNN software simulator.