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Guidance for the Verification and Validation of Neural Networks

Guidance for the Verification and Validation of Neural Networks

Laura L. Pullum, Brian J. Taylor, Marjorie A. Darrah

ISBN: 978-1-119-13467-1

Oct 2015, Wiley-IEEE Computer Society Pr

200 pages

Select type: O-Book

Description

This book provides guidance on the verification and validation of neural networks/adaptive systems. Considering every process, activity, and task in the lifecycle, it supplies methods and techniques that will help the developer or V&V practitioner be confident that they are supplying an adaptive/neural network system that will perform as intended. Additionally, it is structured to be used as a cross-reference to the IEEE 1012 standard.
Preface.

Acknowledgements.

1 Overview.

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.