"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.

Application of Neural Networks in High Assurance Systems: A Survey.- Robust Adaptive Control Revisited: Semi-global Boundedness and Margins.- Network Complexity Analysis of Multilayer Feedforward Artificial Neural Networks.- Design and Flight Test of an Intelligent Flight Control System.- Stability, Convergence, and Verification and Validation Challenges of Neural Net Adaptive Flight Control.- Dynamic Allocation in Neural Networks for Adaptive Controllers.- Immune Systems Inspired Approach to Anomaly Detection, Fault Localization and Diagnosis in Automotive Engines.- Pitch-Depth Control of Submarine Operating in Shallow Water via Neuro-adaptive Approach.- Stick-Slip Friction Compensation Using a General Purpose Neuro-Adaptive Controller with Guaranteed Stability.- Modeling of Crude Oil Blending via Discrete-Time Neural Networks.- Adaptive Self-Tuning Wavelet Neural Network Controller for a Proton Exchange Membrane Fuel Cell.- Erratum to: Network Complexity Analysis of Multilayer Feedforward Artificial Neural Networks.

State of the art of Neural Networks in real-world, safety-critical systems Presents Neural Network applications in safety related areas, ranging from aerospace industry and steam power turbines to the automotive industry Provides a better understanding of the practical requirements for developing and deploying neuro-adaptive systems