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001 u373836
003 SIRSI
005 20160812084205.0
007 cr nn 008mamaa
008 100306s2010 gw | s |||| 0|eng d
020 _a9783642106903
_9978-3-642-10690-3
040 _cMX-MeUAM
050 4 _aTA329-348
050 4 _aTA640-643
082 0 4 _a519
_223
100 1 _aSchumann, Johann.
_eeditor.
245 1 0 _aApplications of Neural Networks in High Assurance Systems
_h[recurso electrónico] /
_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 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=http://link.springer.com/book/10.1007/978-3-642-10690-3
596 _a19
942 _cLIBRO_ELEC
999 _c201716
_d201716