"Applications of Neural Networks in High Assurance Systems" is the first book directly addressing a key part of neural network technology: methods used to pass the tough verification and validation (V&V) standards required in many safety-critical applications. The book presents what kinds of evaluation methods have been developed across many sectors, and how to pass the tests. A new adaptive structure of V&V is developed in this book, different from the simple six sigma methods usually used for large-scale systems and different from the theorem-based approach used for simplified component subsystems.
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"Applications of Neural Networks in High Assurance Systems" is the first book directly addressing a key part of neural network technology: methods used to pass the tough verification and validation (V&V) standards required in many safety-critical applications. The book presents what kinds of evaluation methods have been developed across many sectors, and how to pass the tests. A new adaptive structure of V&V is developed in this book, different from the simple six sigma methods usually used for large-scale systems and different from the theorem-based approach used for simplified component subsystems.
Imprint | Springer-Verlag |
Country of origin | Germany |
Series | Studies in Computational Intelligence, 268 |
Release date | May 2012 |
Availability | Expected to ship within 10 - 15 working days |
First published | 2010 |
Editors | Johann M. Ph. Schumann, Yan Liu |
Dimensions | 235 x 155 x 15mm (L x W x T) |
Format | Paperback |
Pages | 248 |
Edition | 2010 ed. |
ISBN-13 | 978-3-642-26269-2 |
Barcode | 9783642262692 |
Categories | |
LSN | 3-642-26269-4 |