Encyclopedia Of Solid Earth Geophysics

Author: Harsh Gupta
Publisher: Springer Science & Business Media
ISBN: 904818701X
Size: 22.10 MB
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Bibliography Ahl, A., 2003. Automatic 1D inversion of multifrequency airborne
electromagnetic data with artificial neural networks: discussion and a ....
Computational Neural Networks for Geophysical Data Processing. London:
Elsevier.

Seismic Waves And Rays In Elastic Media

Author: Michael A. Slawinski
Publisher: Elsevier
ISBN: 9780080439303
Size: 37.33 MB
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SEISMIC EXPLORATION Editors: Klaus Helbig and Sven Treitel PUBLISHED
VOLUMES 1984 - Mathematical Aspects of ... ISBN 0-08-043649-8 2001 -
Computational Neural Networks for Geophysical Data Processing (M.M. Poulton)
ISBN ...

Expanded Abstracts With Biographies

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Zhang, L., Quirein, J., and Schuelke, J., 2001, “Selforganizing map (SOM) neural
network for classifying seismic traces and picking horizons", in Poulton, M., ed.,
Computational neural networks for geophysical data processing; Chapter l0, ...

Handbook Of Neural Network Signal Processing

Author: Yu Hen Hu
Publisher: CRC Press
ISBN: 1420038613
Size: 63.91 MB
Format: PDF
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You need a handy reference that will inform you of current applications in this new area. The Handbook of Neural Network Signal Processing provides this much needed service for all engineers and scientists in the field.

Geophysical Applications Of Artificial Neural Networks And Fuzzy Logic

Author: W. Sandham
Publisher: Springer Science & Business Media
ISBN: 9781402017292
Size: 62.96 MB
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AUTOMATED PICKING OF SEISMIC FIRST-ARRIVALS WITH NEURAL
NETWORKS DOUGLAS I. HART Western Geophysical, 1625 ... it is possible to
determine the properties of the features input to the neural network that impact
upon the reliability of the picking process. ... of the first-arrival in seismic data, is
essential for performing refraction statics computations or diving-wave
tomography calculations.

Process Neural Networks

Author: Xingui He
Publisher: Springer Science & Business Media
ISBN: 9783540737629
Size: 15.33 MB
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6 Feedback Process Neural NetWorks A feedback neural network is an artificial
neural network model that has been widely applied to signal processing ",
optimal computation", convex nonlinear programming", seismic data filtering", etc.

Monitoring The Comprehensive Nuclear Test Ban Treaty Data Processing And Infrasound

Author: Zoltan A. Der
Publisher: Springer
ISBN: 3034881444
Size: 27.77 MB
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The PIDC has accumulated millions of seismic phase readings for the current
threecomponent stations, which were ... This paper proposes an approach to
training neural networks that takes advantage of accumulated seismic phases ...
Computational modelsof aneural network tryto emulate thephysiology ofreal
neurons.