[Papers] Impacts of Random Telegraph Noise with Various Time Constants and Number of States in Temporal Noise of CMOS Image Sensors

Kuroda, Rihito; Teramoto, Akinobu; Sugawa, Shigetoshi

doi:10.3169/mta.6.171

Cited by 7 publications

(5 citation statements)

References 41 publications

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“…3) If trapping/detrapping processes at a certain defect dominate the LFN characteristics, trap occupancy switching results in a discrete current fluctuation (two or multilevel RTN). [36][37][38] However, a Gaussian distribution of the current amplitude is observed in the sensor. Figure 3d shows the variation of I D over time in the bias condition where the Lorentzianlike noise is observed.…”

Section: Lfn Characteristics Of the Fet-type Gas Sensor With A Wo 3 S...mentioning

confidence: 99%

In‐Memory‐Computed Low‐Frequency Noise Spectroscopy for Selective Gas Detection Using a Reducible Metal Oxide

et al. 2023

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Concerns about indoor and outdoor air quality, industrial gas leaks, and medical diagnostics are driving the demand for high-performance gas sensors. Owing to their structural variety and large surface area, reducible metal oxides hold great promise for constructing a gas-sensing system. While many earlier reports have successfully obtained a sufficient response to various types of target gases, the selective detection of target gases remains challenging. In this work, a novel method, low-frequency noise (LFN) spectroscopy is presented, to achieve selective detection using a single FET-type gas sensor. The LFN of the sensor is accurately modeled by considering the charge fluctuation in both the sensing material and the FET channel. Exposure to different target gases produces distinct corner frequencies of the power spectral density that can be used to achieve selective detection. In addition, a 3D vertical-NAND flash array is used with the fast Fourier transform method via in-memory-computing, significantly improving the area and power efficiency rate. The proposed system provides a novel and efficient method capable of selectively detecting a target gas using in-memory-computed LFN spectroscopy and thus paving the way for the further development in gas sensing systems.

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Section: Lfn Characteristics Of the Fet-type Gas Sensor With A Wo 3 S...mentioning

confidence: 99%

In‐Memory‐Computed Low‐Frequency Noise Spectroscopy for Selective Gas Detection Using a Reducible Metal Oxide

et al. 2023

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“…It has been pointed out that 1/f noise may influence not only analog devices, but also digital devices when device shrinkage and the decreasing signal voltage are moved on [15]. Random telegraph noise (RTN), another low-frequency noise also affects electronic devices, such as CMOS image sensor [16][17][18][19][20][21], static random access memory (SRAM) [22][23][24][25], dynamic random access memory (DRAM) [25], and flash memory [26][27][28][29][30][31][32]. Low-frequency noise, such as 1/f noise and RTN, have high variability [33,34] because they must be statistical phenomena by nature, and statistical analysis is required to fully understand this phenomenon.…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Low-Frequency Noise in MOSFETs Used as a Key Component in Semiconductor Memory Devices

Teramoto

2021

Electronics

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Methods for evaluating low-frequency noise, such as 1/f noise and random telegraph noise, and evaluation results are described. Variability and fluctuation are critical in miniaturized semiconductor devices because signal voltage must be reduced in such devices. Especially, the signal voltage in multi-bit memories must be small. One of the most serious issues in metal-oxide-semiconductor field-effect-transistors (MOSFETs) is low-frequency noise, which occurs when the signal current flows at the interface of different materials, such as SiO2/Si. Variability of low-frequency noise increases with MOSFET shrinkage. To assess the effect of this noise on MOSFETs, we must first understand their characteristics statistically, and then, sufficient samples must be accurately evaluated in a short period. This study compares statistical evaluation methods of low-frequency noise to the trend of conventional evaluation methods, and this study’s findings are presented.

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“…The pixels with high RNs (blinking or twinkling pixels [7][8][9]) will create fixed-pattern temporal noises flickering from frame to frame. It is known that most of the pixels on the long distribution tails show the behavior of the random telegraph signals (RTS) [10][11][12][13][14][15][16][17][18][19][20][21][22][23]. Such noises are called the RTS noises, or the random telegraph noises (RTN).…”

Section: Introductionmentioning

confidence: 99%

“…A general study of the RTS phenomena in semiconductor devices can be found in a recent book [24], covering a wide range of experimental and theoretical topics. For CIS, the most reported RTN originate from the source followers (SF) of the active pixels [10][11][12][13][14][15][16][17][18][19][20][21][22][23]. Although other sources, such as DC-RTS, have been reported [25,26], a comprehensive discrimination and comparison of the various sources of RTN in a CIS cannot be found in the literature yet.…”

Section: Introductionmentioning

confidence: 99%

Random Telegraph Noises from the Source Follower, the Photodiode Dark Current, and the Gate-Induced Sense Node Leakage in CMOS Image Sensors

Chao

Yeh

et al. 2019

Sensors

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In this paper we present a systematic approach to sort out different types of random telegraph noises (RTN) in CMOS image sensors (CIS) by examining their dependencies on the transfer gate off-voltage, the reset gate off-voltage, the photodiode integration time, and the sense node charge retention time. Besides the well-known source follower RTN, we have identified the RTN caused by varying photodiode dark current, transfer-gate and reset-gate induced sense node leakage. These four types of RTN and the dark signal shot noises dominate the noise distribution tails of CIS and non-CIS chips under test, either with or without X-ray irradiation. The effect of correlated multiple sampling (CMS) on noise reduction is studied and a theoretical model is developed to account for the measurement results.

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[Papers] Impacts of Random Telegraph Noise with Various Time Constants and Number of States in Temporal Noise of CMOS Image Sensors

Cited by 7 publications

References 41 publications

In‐Memory‐Computed Low‐Frequency Noise Spectroscopy for Selective Gas Detection Using a Reducible Metal Oxide

In‐Memory‐Computed Low‐Frequency Noise Spectroscopy for Selective Gas Detection Using a Reducible Metal Oxide

Evaluation of Low-Frequency Noise in MOSFETs Used as a Key Component in Semiconductor Memory Devices

Random Telegraph Noises from the Source Follower, the Photodiode Dark Current, and the Gate-Induced Sense Node Leakage in CMOS Image Sensors

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