Computational neural networks for geophysical data processing

• Other Authors: Poulton, Mary M.
• Format: Electronic eBook
• Language: English
• Published: Amsterdam ; New York : Pergamon, 2001.
• Edition: 1st ed.
• Series: Handbook of geophysical exploration. Seismic exploration ; v. 30.
• Subjects: Prospecting > Geophysical methods > Data processing.; Neural networks (Computer science); elektronické knihy; electronic books
• ISBN: 0080439861; 9780080439860; 9780080529653; 0080529658; 1281038091; 9781281038098
• ISSN: 0950-1401 ;
• Physical Description: 1 online resource (xiii, 335 pages) : illustrations

This book was primarily written for an audience that has heard about neural networks or has had some experience with the algorithms, but would like to gain a deeper understanding of the fundamental material. For those that already have a solid grasp of how to create a neural network application, thi...

Table of Contents:

• Front Cover; Computational Neural Networks for Geophysical Data Processing; Copyright Page; Table of Contents; Preface; Contributing Authors; Part I: Introduction to Computational Neural Networks; Chapter 1. A Brief History; Chapter 2. Biological Versus Computational Neural Networks; Chapter 3. Multi-Layer Perceptrons and Back-Propagation Learning; Chapter 4. Design of Training and Testing Sets; Chapter 5. Alternative Architectures and Learning Rules; Chapter 6. Software and Other Resources; Part II: Seismic Data Processing; Chapter 7. Seismic Interpretation and Processing Applications.
• Chapter 8. Rock Mass and Reservoir CharacterizationChapter 9. Identifying Seismic Crew Noise; Chapter 10. Self-Organizing Map (SOM) Network for Tracking Horizons and Classifying Seismic Traces; Chapter 11. Permeability Estimation with an RBF Network and Levenberg-Marquardt Learning; Chapter 12. Caianiello Neural Network Method for Geophysical Inverse Problems; Part III: Non-Seismic Applications; Chapter 13. Non-Seismic A.