1999
DOI: 10.1117/12.354293
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<title>Noise analysis and a comparative study of noise in MEMS and MOEMS</title>

Abstract: 172 1'('((7t t/t(ZI'S !tfiCl'() E1tciro i,zec/uztzzeil sy.st-iits (tiIEA!S) (flU! mzero opto ei(-(tro iruc/ia,zzcaj sijsti'iizs (i!OEiIS) h(Itfr (J1Y)WIL LIZ L1tL)K)it(Z1ZCC, e.SJ)((Z(111?J ZIZ .Sifl(11t structure (lpJ)1Z((ZtZO7ZS. lIZ thzs ja;er a tlieoretzeal C)1flJ)a1atitU .sttidij 2s ifla(h (111(Li7J.271q th1'(-dzfjere7zt tiJ;)es of lflz(VO pressure s4?lsors. A1EALS type pressure-' sensors of 1/u-pZ(ZOresz.stzvt (171(1 (aJ)UCZtZV( t?JJW (ire consz(1(-rf'd aloizg wzth AI'OEAI pi-.ssui sensor of the Fbrj-Pro… Show more

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“…Apart from the usual thermal and shot noise terms in the case of MEMS it is the noise due to Brownian motion that will set the fundamental limit for ultra sensitive pressure sensors. To obtain quantitative results about the fluctuating noise pressure, the Brownian motion is treated as an ergodic random process and the mean square deflection is obtained through a Fourier transform of the autocorrelation function 1,25 .…”
Section: Capacitive Pressure Sensormentioning
confidence: 99%
“…Apart from the usual thermal and shot noise terms in the case of MEMS it is the noise due to Brownian motion that will set the fundamental limit for ultra sensitive pressure sensors. To obtain quantitative results about the fluctuating noise pressure, the Brownian motion is treated as an ergodic random process and the mean square deflection is obtained through a Fourier transform of the autocorrelation function 1,25 .…”
Section: Capacitive Pressure Sensormentioning
confidence: 99%