Title :
Elastic wave propagation modeling on emulated digital CNN-UM architecture
Author :
Kozma, Péter ; Sonkoly, Péter ; Szolgay, Péter
Author_Institution :
Dept. of Image Process. & Neurocomputing, Veszprem Univ., Hungary
Abstract :
The synthetic seismogram has seen many years of widespread and successful application in geophysical prospecting. It is used to simulate the normal incidence reflectivity of a heterogeneous medium and has been employed more recently to obtain the responses of subsurface structural and stratigraphic configurations. The propagation of seismic waves has to be modeled to create synthetic seismograms. The solution of the partial differential equations of motion describing the propagation of stress waves in an elastic medium requires enormous computation power. In this paper a solution of seismic wave propagation will be presented on CNN-UM architecture. Unfortunately the space-dependent equations and the low computational precision do not make it possible to utilize the huge computing power of the analog CNN-UM chips so the Falcon emulated digital CNN-UM architecture is used to implement our solution.
Keywords :
cellular neural nets; geophysics computing; partial differential equations; seismic waves; wave propagation; cellular neural network universal machine; elastic wave propagation modeling; emulated digital CNN-UM architecture; partial differential equations; seismic waves; space-dependent equation; stress waves; synthetic seismogram; Analog computers; Cellular neural networks; Computer architecture; Geophysics computing; Image processing; Numerical models; Partial differential equations; Seismic waves; Stress; Very large scale integration; Elastic Wave Propagation; Emulated Digital CNN-UM;
Conference_Titel :
Cellular Neural Networks and Their Applications, 2005 9th International Workshop on
Print_ISBN :
0-7803-9185-3
DOI :
10.1109/CNNA.2005.1543177