Guidance for the Verification and Validation of Neural Networks

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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.

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Contents

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1
Verification and Validation of Neural Networks Guidance
39
Recent Changes to IEEE Std 1012
111
Copyright

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About the author (2007)

Dr. Laura L. Pullum is a Principal Research Scientist and Technical Director at Lockheed Martin in Eagan, MN. Her areas of research and development include software and system dependability, verification and validation, adaptive systems, and automated reasoning.

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.

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