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Springer Applications of Neural Networks in High Assurance Systems

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Description

Applications of Neural Networks in High Assurance Systems is the first book directly addressing verification and validation (V&V) standards for neural network technology in safety-critical applications. This comprehensive guide from Springer presents evaluation methods developed across multiple sectors and demonstrates how to meet rigorous testing requirements. The book develops a new adaptive V&V structure, moving beyond traditional six sigma approaches used for large-scale systems and theorem-based methods for simplified components. It covers practical strategies for implementing neural networks in high assurance environments where reliability and safety certification are non-negotiable. Whether you work in aviation, automotive, medical devices, or other safety-critical industries, this volume provides essential insights into integrating advanced neural network capabilities while maintaining compliance with stringent regulatory standards.

Key Features

The book addresses neural network verification and validation methods specifically designed for safety-critical applications and high assurance systems.

Springer's publication includes evaluation approaches developed across multiple industrial sectors, offering diverse practical perspectives.

This volume presents an adaptive V&V structure that differs from conventional six sigma methodologies and traditional theorem-based approaches.

Applications of Neural Networks in High Assurance Systems covers how to pass rigorous testing requirements in regulated industries.

Product Specifications

Model
9478649
Format
hardcover
Domain
Amazon UK
Release Date
28 February 2010
Listed Since
27 October 2009

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