Seismic Waves And Rays In Elastic Media

Author: Michael A. Slawinski
Publisher: Elsevier
ISBN: 9780080439303
Size: 30.70 MB
Format: PDF, ePub, Mobi
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3d Updated and Revised Edition (B.A. Hardage) ISBN 0-08-043518-1 2001 -
Seismic Signatures and Analysis of Reflection Data in Anisotropic Media (I.
Tsvankin) ISBN 0-08-043649-8 2001 - Computational Neural Networks for
Geophysical Data Processing (M.M. Poulton) ISBN 0-08-043986-1 2001 - Wave
Fields in Real Media: Wave Propagation in Anisotropic, Anelastic and Porous
Media (J.M. Carcione) ISBN 0-08-043929-2 2002 - Multi-Component VSP
Analysis for Applied ...

Handbook Of Neural Network Signal Processing

Author: Yu Hen Hu
Publisher: CRC Press
ISBN: 1420038613
Size: 34.25 MB
Format: PDF, Mobi
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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.

Soft Computing In Machine Learning

Author: Sang-Yong Rhee
Publisher: Springer
ISBN: 331905533X
Size: 50.65 MB
Format: PDF
View: 4706
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In the paper “adjacency cube” method for integration of results of few
interpretation algorithms is proposed. Learning algorithm for the “adjacency cube
” with low computational complexity was developed. The proposed method
improves quality of recognition by 2-3 percent. Keywords: Geophysical research
of boreholes, machine learning, artificial neural network, k-NN, uranium deposit,
post-processing data, learning sample, “adjacency cube” method. 1 Introduction
This problem of ...

Process Neural Networks

Author: Xingui He
Publisher: Springer Science & Business Media
ISBN: 9783540737629
Size: 25.48 MB
Format: PDF, Docs
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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.
A traditional feedback neural network model generally has time-invariant inputs.
However, when a biological neural organization processes information, it actually
feeds back time-delay information and the inputs of external signals will last for a
period ...

Proceedings Of The International Conference On Neural Networks

Author: Institute of Electrical and Electronics Engineers
ISBN: 9780780341234
Size: 42.65 MB
Format: PDF, ePub
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Abstract We train an artificial neural network to perform decon- volution of seismic
data and thereby recognize and remove multiple arrivals in reflection seismic
data. Basis for the learning process is a well log that is typical for the area in
which the data were gathered. Modeling data from this well log and comparing it
to real recorded data allows deduce relations between the subsurface model in
the recorded data. In contrast to conventional geophysical data processing
techniques, ...

Time Series Analysis And Applications To Geophysical Systems

Author: David Brillinger
Publisher: Springer Science & Business Media
ISBN: 9780387223117
Size: 66.34 MB
Format: PDF, Docs
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Further, the computational efficiency and advantage of RBF-AR models over RBF
neural network models is demonstrated in real data analysis of EEG time series
of subjects with epilepsy. The advantage of multivariate RBF-ARX models in the
modeling of thermal power plants is also shown using numerical results. Key
words. Innovation approach, maximum likelihood method, nonlinear Kalman filter
, Markov diffusion process, Pearson system, Gamma distributed processes,
stochastic ...