Verification And Validation Of Neural Networks For Aerospace Systems

Verification and Validation of Neural Networks for Aerospace Systems

Verification and Validation of Neural Networks for Aerospace Systems

The Dryden Flight Research Center V&V working group and NASA Ames Research Center Automated Software Engineering (ASE) group collaborated to prepare this report. The purpose is to describe V&V processes and methods for certification of neural networks for aerospace applications, particularly adaptive flight control systems like Intelligent Flight Control Systems (IFCS) that use neural networks. This report is divided into the following two sections: 1) Overview of Adaptive Systems; and 2) V&V Processes/Methods.Mackall, Dale and Nelson, Stacy and Schumman, Johann and Clancy, Daniel (Technical Monitor)Ames Research Center; Armstrong Flight Research CenterAEROSPACE SYSTEMS; NEURAL NETS; SOFTWARE ENGINEERING; PROGRAM VERIFICATION (COMPUTERS); ADAPTIVE CONTROL; FLIGHT CONTROL; PERFORMANCE TESTS; COMPUTERIZED SIMULATION; SENSITIVITY ANALYSIS; AIRCRAFT STRUCTURES

Guidance for the Verification and Validation of Neural Networks

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.