000			03441nam a22005175i 4500
001			978-3-642-10690-3
003			DE-He213
005			20140220084529.0
007			cr nn 008mamaa
008			100306s2010 gw | s |||| 0|eng d
020			_a9783642106903 _9978-3-642-10690-3
024	7		_a10.1007/978-3-642-10690-3 _2doi
050		4	_aTA329-348
050		4	_aTA640-643
072		7	_aTBJ _2bicssc
072		7	_aMAT003000 _2bisacsh
082	0	4	_a519 _223
100	1		_aSchumann, Johann. _eeditor.
245	1	0	_aApplications of Neural Networks in High Assurance Systems _h[electronic resource] / _cedited by Johann Schumann, Yan Liu.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2010.
300			_a280p. 99 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aStudies in Computational Intelligence, _x1860-949X ; _v268
505	0		_aApplication 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.
520			_a"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.
650		0	_aEngineering.
650		0	_aArtificial intelligence.
650		0	_aEngineering mathematics.
650		0	_aIndustrial engineering.
650	1	4	_aEngineering.
650	2	4	_aAppl.Mathematics/Computational Methods of Engineering.
650	2	4	_aArtificial Intelligence (incl. Robotics).
650	2	4	_aAutomotive Engineering.
650	2	4	_aIndustrial and Production Engineering.
700	1		_aLiu, Yan. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642106897
830		0	_aStudies in Computational Intelligence, _x1860-949X ; _v268
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-642-10690-3
912			_aZDB-2-ENG
999			_c111769 _d111769