Guidance for the Verification and Validation of Neural Networks
March 2007, Wiley-IEEE Computer Society Press
1.1 Definitions and Conventions.
1.2 Organization of the Book.
2 Areas of Consideration for Adaptive Systems.
2.1 Safety-Critical Adaptive System Example and Experience.
2.2 Hazard Analysis.
2.3 Requirements for Adaptive Systems.
2.4 Rule Extraction.
2.5 Modified Life Cycle for Developing Neural Networks.
2.6 Operational Monitors.
2.7 Testing Considerations.
2.8 Training Set Analysis.
2.9 Stability Analysis
2.10 Configuration Management of Neural Network Training and Design.
2.11 Simulation of Adaptive Systems.
2.12 Neural Network Visualization.
2.13 Adaptive System and Neural Network Selection.
3 Verification and Validation of Neural Networks—Guidance.
3.1 Process: Management.
3.2 Process: Acquisition.
3.3 Process: Supply.
3.4 Process: Development.
3.5 Process: Operation.
3.6 Process: Maintenance.
4 Recent Changes to IEEE Std 1012.
Appendix A: References.
Appendix B: Acronyms.
Appendix C: Definitions.
Brian J. Taylor served as a Principal Member Research Staff for the Institute for Scientific Research, working with a research team on the development, implementation, and flight qualification of Intelligent Flight Control Systems. He is currently a PhD candidate.
Dr. Marjorie A. Darrah is a Principal Scientist for the West Virginia High Technology Consortium Foundation. Her areas of research and development include virtual reality, education, data mining, software verification and validation, algorithm development, and neural networks.