| Preface | |
| Contributing Authors | |
| Pt. I | Introduction to Computational Neural Networks | 1 |
| Ch. 1 | A Brief History | 3 |
| Ch. 2 | Biological Versus Computational Neural Networks | 19 |
| Ch. 3 | Multi-Layer Perceptrons and Back-Propagation Learning | 27 |
| Ch. 4 | Design of Training and Testing Sets | 55 |
| Ch. 5 | Alternative Architectures and Learning Rules | 66 |
| Ch. 6 | Software and Other Resources | 89 |
| Pt. II | Seismic Data Processing | 99 |
| Ch. 7 | Seismic Interpretation and Processing Applications | 101 |
| Ch. 8 | Rock Mass and Reservoir Characterization | 119 |
| Ch. 9 | Identifying Seismic Crew Noise | 129 |
| Ch. 10 | Self-Organizing Map (SOM) Network for Tracking Horizons and Classifying Seismic Traces | 155 |
| Ch. 11 | Permeability Estimation with an RBF Network and Levenberg-Marquardt Learning | 171 |
| Ch. 12 | Caianiello Neural Network Method for Geophysical Inverse Problems | 187 |
| Pt. III | Non-Seismic Applications | 217 |
| Ch. 13 | Non-Seismic Applications | 219 |
| Ch. 14 | Detection of AEM Anomalies Corresponding to Dike Structures | 234 |
| Ch. 15 | Locating Layer Boundaries with Unfocused Resistivity Tools | 257 |
| Ch. 16 | A Neural Network Interpretation System for Near-Surface Geophysics Electromagnetic Ellipticity Soundings | 286 |
| Ch. 17 | Extracting IP Parameters From TEM Data | 307 |
| Author Index | 327 |
| Index | 331 |
Format: Hardcover, 350 pages
