Cargando…
Guidance for the verification and validation of neural networks
Guidance for the Verification and Validation of Neural Networks is a supplement to the IEEE Standard for Software Verification and Validation, IEEE Std 1012-1998. Born out of a need by the National Aeronautics and Space Administration's safety- and mission-critical research, this book compiles...
Autores principales: | , , |
---|---|
Lenguaje: | eng |
Publicado: |
Wiley-IEEE Press
2007
|
Materias: | |
Acceso en línea: | http://cds.cern.ch/record/2116410 |
_version_ | 1780949208912625664 |
---|---|
author | Pullum, L Taylor, B Darrah, M |
author_facet | Pullum, L Taylor, B Darrah, M |
author_sort | Pullum, L |
collection | CERN |
description | Guidance for the Verification and Validation of Neural Networks is a supplement to the IEEE Standard for Software Verification and Validation, IEEE Std 1012-1998. Born out of a need by the National Aeronautics and Space Administration's safety- and mission-critical research, this book compiles over five years of applied research and development efforts. It is intended to assist the performance of verification and validation (V&V) activities on adaptive software systems, with emphasis given to neural network systems. The book discusses some of the difficulties with trying to assure adaptive systems in general, presents techniques and advice for the V&V practitioner confronted with such a task, and based on a neural network case study, identifies specific tasking and recommendations for the V&V of neural network systems. |
id | cern-2116410 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2007 |
publisher | Wiley-IEEE Press |
record_format | invenio |
spelling | cern-21164102021-04-21T19:56:47Zhttp://cds.cern.ch/record/2116410engPullum, LTaylor, BDarrah, MGuidance for the verification and validation of neural networksEngineeringGuidance for the Verification and Validation of Neural Networks is a supplement to the IEEE Standard for Software Verification and Validation, IEEE Std 1012-1998. Born out of a need by the National Aeronautics and Space Administration's safety- and mission-critical research, this book compiles over five years of applied research and development efforts. It is intended to assist the performance of verification and validation (V&V) activities on adaptive software systems, with emphasis given to neural network systems. The book discusses some of the difficulties with trying to assure adaptive systems in general, presents techniques and advice for the V&V practitioner confronted with such a task, and based on a neural network case study, identifies specific tasking and recommendations for the V&V of neural network systems.Wiley-IEEE Pressoai:cds.cern.ch:21164102007 |
spellingShingle | Engineering Pullum, L Taylor, B Darrah, M Guidance for the verification and validation of neural networks |
title | Guidance for the verification and validation of neural networks |
title_full | Guidance for the verification and validation of neural networks |
title_fullStr | Guidance for the verification and validation of neural networks |
title_full_unstemmed | Guidance for the verification and validation of neural networks |
title_short | Guidance for the verification and validation of neural networks |
title_sort | guidance for the verification and validation of neural networks |
topic | Engineering |
url | http://cds.cern.ch/record/2116410 |
work_keys_str_mv | AT pulluml guidancefortheverificationandvalidationofneuralnetworks AT taylorb guidancefortheverificationandvalidationofneuralnetworks AT darrahm guidancefortheverificationandvalidationofneuralnetworks |