000			03113nam a22004815i 4500
001			978-1-4419-6606-3
003			DE-He213
005			20140220084510.0
007			cr nn 008mamaa
008			100917s2010 xxu| s |||| 0|eng d
020			_a9781441966063 _9978-1-4419-6606-3
024	7		_a10.1007/978-1-4419-6606-3 _2doi
050		4	_aTK7888.4
072		7	_aTJFC _2bicssc
072		7	_aTEC008010 _2bisacsh
082	0	4	_a621.3815 _223
100	1		_aSinghee, Amith. _eeditor.
245	1	0	_aExtreme Statistics in Nanoscale Memory Design _h[electronic resource] / _cedited by Amith Singhee, Rob A. Rutenbar.
250			_a1.
264		1	_aBoston, MA : _bSpringer US : _bImprint: Springer, _c2010.
300			_aX, 246 p. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aIntegrated Circuits and Systems, _x1558-9412
505	0		_aExtreme Statistics in Memories -- Statistical Nano CMOS Variability and Its Impact on SRAM -- Importance Sampling-Based Estimation: Applications to Memory Design -- Direct SRAM Operation Margin Computation with Random Skews of Device Characteristics -- Yield Estimation by Computing Probabilistic Hypervolumes -- Most Probable Point-Based Methods -- Extreme Value Theory: Application to Memory Statistics.
520			_aExtreme Statistics in Nanoscale Memory Design brings together some of the world’s leading experts in statistical EDA, memory design, device variability modeling and reliability modeling, to compile theoretical and practical results in one complete reference on statistical techniques for extreme statistics in nanoscale memories. The work covers a variety of techniques, including statistical, deterministic, model-based and non-parametric methods, along with relevant description of the sources of variations and their impact on devices and memory design. Specifically, the authors cover methods from extreme value theory, Monte Carlo simulation, reliability modeling, direct memory margin computation and hypervolume computation. Ideas are also presented both from the perspective of an EDA practitioner and a memory designer to provide a comprehensive understanding of the state-of -the-art in the area of extreme statistics estimation and statistical memory design. Extreme Statistics in Nanoscale Memory Design is a useful reference on statistical design of integrated circuits for researchers, engineers and professionals.
650		0	_aEngineering.
650		0	_aElectronics.
650		0	_aSystems engineering.
650	1	4	_aEngineering.
650	2	4	_aCircuits and Systems.
650	2	4	_aElectronics and Microelectronics, Instrumentation.
700	1		_aRutenbar, Rob A. _eeditor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9781441966056
830		0	_aIntegrated Circuits and Systems, _x1558-9412
856	4	0	_uhttp://dx.doi.org/10.1007/978-1-4419-6606-3
912			_aZDB-2-ENG
999			_c110667 _d110667