000 03819nam a22006015i 4500
001 978-0-387-25903-1
003 DE-He213
005 20161121231013.0
007 cr nn 008mamaa
008 100301s2005 xxu| s |||| 0|eng d
020 _a9780387259031
_9978-0-387-25903-1
024 7 _a10.1007/b136458
_2doi
050 4 _aTK7888.4
072 7 _aTJFC
_2bicssc
072 7 _aTEC008010
_2bisacsh
082 0 4 _a621.3815
_223
100 1 _aDallet, Dominique.
_eauthor.
245 1 0 _aDynamic Characterisation of Analogue-to-Digital Converters
_h[electronic resource] /
_cby Dominique Dallet, José Machado da Silva.
264 1 _aBoston, MA :
_bSpringer US,
_c2005.
300 _aXX, 280 p.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aThe International Series in Engineering and Computer Science, Analog Circuits and Signal Processing,
_x0893-3405 ;
_v860
505 0 _aADC Characterisation Based on Sinewave Analysis -- ADC Applications, Architectures and Terminology -- Sinewave Test Setup -- Time-Domain Data Analysis -- Frequency-Domain Data Analysis -- Code Histogram Test -- Comparative Study of ADC Sinewave Test Methods -- Measurement of Additional Parameters -- Jitter Measurement -- Differential Gain and Phase Testing -- Step and Transient Response Measurement -- Hysteresis Measurement.
520 _aThe Analogue-to-digital converter (ADC) is the most pervasive block in electronic systems. With the advent of powerful digital signal processing and digital communication techniques, ADCs are fast becoming critical components for system’s performance and flexibility. Knowing accurately all the parameters that characterise their dynamic behaviour is crucial, on one hand to select the most adequate ADC architecture and characteristics for each end application, and on the other hand, to understand how they affect performance bottlenecks in the signal processing chain. Dynamic Characterisation of Analogue-to-Digital Converters presents a state of the art overview of the methods and procedures employed for characterising ADCs’ dynamic performance behaviour using sinusoidal stimuli. The three classical methods – histogram, sine wave fitting, and spectral analysis – are thoroughly described, and new approaches are proposed to circumvent some of their limitations. This is a must-have compendium, which can be used by both academics and test professionals to understand the fundamental mathematics underlining the algorithms of ADC testing, and as an handbook to help the engineer in the most important and critical details for their implementation.
650 0 _aEngineering.
650 0 _aPhysical measurements.
650 0 _aMeasurement.
650 0 _aEngineering design.
650 0 _aElectrical engineering.
650 0 _aMicrowaves.
650 0 _aOptical engineering.
650 0 _aElectronics.
650 0 _aMicroelectronics.
650 0 _aElectronic circuits.
650 1 4 _aEngineering.
650 2 4 _aCircuits and Systems.
650 2 4 _aElectrical Engineering.
650 2 4 _aEngineering Design.
650 2 4 _aElectronics and Microelectronics, Instrumentation.
650 2 4 _aMicrowaves, RF and Optical Engineering.
650 2 4 _aMeasurement Science and Instrumentation.
700 1 _aSilva, José Machado da.
_eauthor.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9780387259024
830 0 _aThe International Series in Engineering and Computer Science, Analog Circuits and Signal Processing,
_x0893-3405 ;
_v860
856 4 0 _uhttp://dx.doi.org/10.1007/b136458
912 _aZDB-2-ENG
950 _aEngineering (Springer-11647)
999 _c507122
_d507122