Response of Correlated Double Sampling CMOS Imager Circuit to Random Telegraph Signal Noise

Leyris, C.; Vildeuil, J.C.; Roy, F.; Mart́ınez, F.; Valenza, M.; Hoffmann, A.

doi:10.1109/iccdcs.2006.250845

Cited by 18 publications

(13 citation statements)

References 15 publications

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“…2(a). The sampler is often implemented to perform correlated double sampling (CDS) to reject offset signal and some types of noise [6,7]. It may operate by first sampling a reference voltage level just after reset release, and then by sampling the signal at the end of integration.…”

Section: Signal Description and Transformationmentioning

confidence: 99%

Cyclostationarity-based model for noise analysis of charge amplification with correlated double sampling

Pittet

Quiquerez

et al. 2009

Analog Integr Circ Sig Process

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A cyclostationarity-based analytical model for noise analysis of charge amplification with correlated double sampling (CDS) is proposed. It is established by signal description and transformation with considerations of input referred noise sources. It predicts that CDS operation has different noise effects: it suppresses reset noise and attenuates 1/f noise from the equivalent input noise voltage, but it has no noise-reduction effect on the input referred noise current. Parametrical analysis can also be performed by using this model. For example, by varying integration duration, the signal-to-noise ratio (SNR) will first be proportional to t int , then to t int , and finally limited by the 1/f noise component becoming predominant. This proposed model is validated by comparison of analysis results with those from temporal noise analysis using SpectreRF of Cadence TM CAD tool. Unlike time-hungry temporal noise analysis, this model provides rapid results.

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Section: Signal Description and Transformationmentioning

confidence: 99%

Cyclostationarity-based model for noise analysis of charge amplification with correlated double sampling

Pittet

Quiquerez

et al. 2009

Analog Integr Circ Sig Process

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“…Kirton and Uren interpreted these findings by a voltage dependent capture cross section, but only proposed different hypotheses for its explanation, one of them being the screening of the trapped charge according to the operating condition of the device [2]. Usually, for semiconductor devices the 1/f noise and the RTS fluctuations are associated with conductivity fluctuations [3]. In the case of MOSFETs, these variations may be associated with two major theories to explain the physical origins of flicker (l/f) noise in MOSFETs transistors.…”

Section: Introductionmentioning

confidence: 96%

Traps centers impact on Silicon nanocrystal memories given by Random Telegraph Signal and low frequency noise

Trabelsi

Militaru

Sghaier³

et al. 2011

Solid-State Electronics

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“…And the vertical-axis and horizontal-axis represent the number of pixels and Digital Number (DN) of NL respectively. Secondly, the noise histogram of a CIS with not only the Gaussian component noise but also the non-Gaussian component noise is calculated based on the work in [4], [11], [14], [28]- [31] and determined by the exponential distribution with two parameter α and β, which is shown in Fig. 10.…”

Section: Rts Noise Modeling In Spatial Domainmentioning

confidence: 99%

“…7. The number of pixels with NL = x, P RTS is given as (11), (11) where α and β are coefficients related to the scale parameter and the slope parameter of the spatial distribution of the RTS noise respectively. To build up the noise histogram in Fig.…”

Section: Rts Noise Modeling In Spatial Domainmentioning

confidence: 99%

“…In the previous works based on Shockley-Read-Hall model [5], the theoretical foundation of RTS noise, a probability density function (PDF) or a noise power spectral density (P.S.D) function of the observed signal used to be calculated in time domain [6]- [8] or in frequency domain [4], [9]- [11]. Besides, Konczakowska [3], [12] proposes a novel approach to identify RTS noise of semiconductor devices.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Modeling and Evaluating for RTS Noise on CMOS Image Sensor in Motion Picture

Deng

Ryu

Nishimura

2010

IEICE Trans. Inf. & Syst.

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SUMMARYThe precise noise modeling of complementary metal oxide semiconductor image sensor (CMOS image sensor: CIS) is a significant key in understanding the noise source mechanisms, optimizing sensor design, designing noise reduction circuit, and enhancing image quality. Therefore, this paper presents an accurate random telegraph signal (RTS) noise analysis model and a novel quantitative evaluation method in motion picture for the visual sensory evaluation of CIS. In this paper, two main works will be introduced. One is that the exposure process of a video camera is simulated, in which a Gaussian noise and an RTS noise in pinnedphotodiode CMOS pixels are modeled in time domain and spatial domain; the other is that a new video quality evaluation method for RTS noise is proposed. Simulation results obtained reveal that the proposed noise modeling for CIS can approximate its physical process and the proposed video quality evaluation method for RTS noise performs effectively as compared to other evaluation methods. Based on the experimental results, conclusions on how the spatial distribution of an RTS noise affects the quality of motion picture are carried out. key words: CMOS image sensor, noise modeling, random telegraph signal noise, video quality

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Response of Correlated Double Sampling CMOS Imager Circuit to Random Telegraph Signal Noise

Cited by 18 publications

References 15 publications

Cyclostationarity-based model for noise analysis of charge amplification with correlated double sampling

Cyclostationarity-based model for noise analysis of charge amplification with correlated double sampling

Traps centers impact on Silicon nanocrystal memories given by Random Telegraph Signal and low frequency noise

A Novel Modeling and Evaluating for RTS Noise on CMOS Image Sensor in Motion Picture

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