Title :
Training two-layer neural network model for tomography data processing
Author_Institution :
Far Eastern State Tech. Univ., Vladivostok, Russia
Abstract :
Presents a training two-layer neural network model for tomography data processing. This model allows one to reconstruct the physical field parameters distribution by using tomography integral data
Keywords :
feedforward neural nets; geophysical signal processing; geophysical techniques; inverse problems; learning (artificial intelligence); physics computing; signal processing; tomography; feedforward neural net; geophysical signal processing; measurement technique; neural network model; physical field parameters distribution; physics computing; selftraining; signal processing; tomography; tomography data processing; tomography integral data; training; two-layer neural network; Acceleration; Computer applications; Concurrent computing; Data processing; Instruments; Neural networks; Neurons; Optical fiber networks; Reconstruction algorithms; Tomography;
Conference_Titel :
OCEANS '95. MTS/IEEE. Challenges of Our Changing Global Environment. Conference Proceedings.
Conference_Location :
San Diego, CA
Print_ISBN :
0-933957-14-9
DOI :
10.1109/OCEANS.1995.528900
