000			04103nam a2200589 i 4500
001			7304003
003			IEEE
005			20220712205923.0
006			m o d
007			cr |n|||||||||
008			151222s2015 njua ob 001 eng d
010			_z 2010277955 (print)
015			_zGBA874568 (print)
016			_z013696212 (print)
020			_a9781119134671 _qelectronic
020			_a047008457X
020			_z9780470084571 _qprint
024	7		_a10.1002/9781119134671 _2doi
035			_a(CaBNVSL)mat07304003
035			_a(IDAMS)0b00006484a80f83
040			_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL
050		4	_aQA76.87 _b.P845 2007eb
082	0	4	_a006.32 _222
100	1		_aPullum, Laura L., _eauthor. _928723
245	1	0	_aGuidance for the verification and validation of neural networks / _cLaura L. Pullum, Brian J. Taylor, Majorie A. Darrah.
264		1	_aHoboken, New Jersey : _bIEEE Computer Society, _cc2007.
264		2	_a[Piscataqay, New Jersey] : _bIEEE Xplore, _c[2015]
300			_a1 PDF (ix, 133 pages) : _billustrations.
336			_atext _2rdacontent
337			_aelectronic _2isbdmedia
338			_aonline resource _2rdacarrier
490	1		_aEmerging technologies
504			_aIncludes bibliographical references (p. 119-121) and index.
505	0		_aAreas of consideration for adaptive systems -- Verification and validation of neural networks-guidance -- Recent changes to IEEE std 1012.
506	1		_aRestricted to subscribers or individual electronic text purchasers.
520			_aGuidance for the Verification and Validation of Neural Networks is a supplement to the IEEE Standard for Software Verification and Validation, IEEE Std 1012-1998. Born out of a need by the National Aeronautics and Space Administration's safety- and mission-critical research, this book compiles over five years of applied research and development efforts. It is intended to assist the performance of verification and validation (V&V) activities on adaptive software systems, with emphasis given to neural network systems. The book discusses some of the difficulties with trying to assure adaptive systems in general, presents techniques and advice for the V&V practitioner confronted with such a task, and based on a neural network case study, identifies specific tasking and recommendations for the V&V of neural network systems. "As the demand for developing and assuring adaptive systems grows, this guidebook will provide practitioners with the insight and practical steps for verifying and validating neural networks. The work of the authors is a great step forward, offering a level of practical experience and advice for the software developers, assurance personnel, and those performing verification and validation of adaptive systems. This guide makes possible the daunting task of assuring this new technology. NASA is proud to sponsor such a realistic approach to what many might think a very futuristic subject. But adaptive systems with neural networks are here today and as the NASA Manager for Software Assurance and Safety, I believe this work by the authors will be a great resource for the systems we are building today and into tomorrow." -Martha S. Wetherholt, NASA Manager of Software Assurance and Software Safety NASA Headquarters, Office of Safety & Mission Assurance.
530			_aAlso available in print.
538			_aMode of access: World Wide Web
588			_aDescription based on PDF viewed 12/22/2015.
650		0	_aNeural networks (Computer science) _93414
650		0	_aComputer programs _xValidation. _928724
650		0	_aComputer programs _xVerification. _928725
655		0	_aElectronic books. _93294
700	1		_aTaylor, Brian J. _928726
700	1		_aDarrah, Majorie A. _928727
710	2		_aIEEE Xplore (Online Service), _edistributor. _928728
710	2		_aWiley, _epublisher. _928729
776	0	8	_iPrint version: _z9780470084571
830		0	_aEmerging technologies _928730
856	4	2	_3Abstract with links to resource _uhttps://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=7304003
942			_cEBK
999			_c74425 _d74425