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Reset noise sets a fundamental detection limit on capacitive sensors. Many sensing circuits depend on accumulating charge on a capacitor as the sensing method. Reset noise is the noise that occurs when the capacitor is reset prior to the charge accumulation cycle. Therefore, it is important to understand the factors which determine reset noise, and...
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Citations
... Noise can originate from various factors, primarily from prolonged exposure and high sensitivity. Types of noise include Gaussian noise [14]- [16], Salt and Pepper noise [17]- [19], uniform noise [20]- [22], photon noise [23]- [25], readout noise [26]- [28], reset noise [29]- [31], quantization noise [32]- [34], and more [35]- [37]. To mitigate such noise, noise filters are employed. ...
span>This paper explores using cameras aimed at the accelerator and brake pedals during sudden unintended acceleration in cars, removing noise from captured images to determine driver incompetence. A car model was constructed using Raspberry Pi to simulate brake malfunction using random functions, increasing the revolutions per minute (RPM) to simulate sudden acceleration. By employing a DC encoder motor to measure the motor's rotational speed through waveform counts, the RPM was calculated. The study recognized sudden acceleration when the brake malfunctioned through the DC encoder motor, causing an abnormal RPM increase, allowing camera capture toward the accelerator and brake during sudden acceleration events. Precautions were taken for problems arising from noise in captured images. The Unix operating system was utilized to apply Gaussian filter image processing techniques for noise removal. While using an average value filter led to abrupt changes by replacing with the average of surrounding signals, resulting in an unsmooth image, a Gaussian filter was used in this study to decrease weights as distance from the center increased, mitigating these issues.</span
... In case of electro-mechanical feedback, if the loop gain is large, non-idealities of the microphone are strongly attenuated and the overall sensitivity of the microphone as well as the interface circuit is determined by the components used to produce the forcefeedback van Roermund et al. (2012). When we retreat from the pure electro-mechanical feedback, a feedback loop can improve offset cancellation and RI dynamic range Fowler, Godfrey, and Mims (2006); Zhang et al. (2012). ...
In this article, evaluation results of the readout interface (RI) for a capacitive MEMS microphone are presented and compared to other works. These experimental results were obtained by measurement of the prototype chips fabricated in a standard 0.35 μm CMOS technology. Moreover, the measurement results are compared to simulations and observed correlation is discussed. The main parameters and features demonstrate excellent performance of the developed RI, mainly in terms of low harmonic distortion (–62.3 dB), low noise floor ( 5.3e−3 aF/Hz) and high dynamic range (110 dB) of the developed readout circuit, which represent a significant improvement with respect to the state-of-the-art solutions.
... Techniques such as capacitive control, bandwidth control, and charge control [23] are used to reduce reset noise. Furthermore, ΔΣ modulator and digital filter are also utilized to process the output of capacitive transimpedance amplifier (CTIA) [24] to achieve less noise. ...
A mobile-based high sensitivity absorptiometer is presented to detect organophosphorus (OP) compounds for Internet-of-Things based food safety tracking. This instrument consists of a customized sensor front-end chip, LED-based light source, low power wireless link, and coin battery, along with a sample holder packaged in a recycled format. The sensor front-end integrates optical sensor, capacitive transimpedance amplifier, and a folded-reference pulse width modulator in a single chip fabricated in a 0.18 μ m 1-poly 5-metal CMOS process and has input optical power dynamic range of 71 dB, sensitivity of 3.6 nW/cm ² (0.77 pA), and power consumption of 14.5 μ W. Enabled by this high sensitivity sensor front-end chip, the proposed absorptiometer has a small size of 96 cm ³ , with features including on-field detection and wireless communication with a mobile. OP compound detection experiments of the handheld system demonstrate a limit of detection (LOD) of 0.4 μ mol/L, comparable to that of a commercial spectrophotometer. Meanwhile, an android-based application (APP) is presented which makes the absorptiometer access to the Internet-of-Things (IoT).
... A feedback loop can be successfully exploited for offset cancellation and the dynamic range enhancement [24][25]. The reset noise reduction schemes [26] also include a feedback loop that either cancels the reset noise or reduces the bandwidth of noise or controls the reset process itself. Interesting concept was presented in [27], where electro-mechanic feedback incorporates a triangle voltage wave generator. ...
... Therefore, main advantages include broad dynamic range, low power consumption and robustness against the environmental noise. However, the vast majority of realizations do not meet the readout circuit requirements for MEMS microphones [22][23][24][25][26][27]. ...
This paper deals with a frontend part of the readout circuit developed as an integrated circuit that after bonding together with a MEMS capacitive microphone (MCM) chip will be used in a noise dosimeter applicable in very noisy and harsh environment, e.g. mine. Therefore, the main attention has been paid to the high dynamic range, low offset and low noise of the developed readout interface as well as its low-power consumption feature. For conversion of the MCM’s capacitance variation into voltage, an approach based on the buffered input conversion stage biased by a voltage divider was used. The advantage of this approach is that the voltage divider formed by MOS transistors can be connected to the high-impedance node (i.e. the output of the MCM, in this case). The whole frontend part of the readout interface was designed in a standard 0.35mm CMOS technology. Finally, the achieved results are discussed and compared to other works.
... To cope with these errors, correlated double sampling (CDS) has proved to be an excellent solution [51]- [53], [61]. CDS is the most frequently used technique for reset noise reduction, although other schemes can be used [62]. This manuscript includes preliminary noise analysis of CDS in discrete-time current sensing we presented in [63]. ...
Current sensing readout is one of the most frequent techniques used in biosensing due to the charge-transfer phenomena occurring at solid-liquid interfaces. The development of novel nanodevices for biosensing determines new challenges for electronic interface design based on current sensing, especially when compact and efficient arrays need to be organized, such as in recent trends of rapid label-free electronic detection of DNA synthesis. This paper will review the basic noise limitations of current sensing interfaces with particular emphasis on integrated CMOS technology. Starting from the basic theory, the paper presents, investigates and compares charge-sensitive amplifier architectures used in both continuous-time and discrete-time approaches, along with their design trade-offs involving noise floor, sensitivity to stray capacitance and bandwidth. The ultimate goal of this review is providing analog designers with helpful design rules and analytical tools. Also, in order to present a comprehensive overview of the state-of-the-art, the most relevant papers recently appeared in the literature about this topic are discussed and compared.
... Hence, the noise due to the random trapping of charge carriers in semiconductors and transistors is usually referred to as RTS noise [3]. Low-frequency and RTS noise is a major concern in the design of electronic circuits used in RF applications (low-noise amplifiers, mixers, oscillators, PLLs, etc.) and CMOS image sensors [4], [5], [6]. Moreover, due to technology scaling, low-frequency noise in MOSFETs is emerging as a source of great concern in the design of even digital circuits such as SRAMs and DRAMs [7], [8]. ...
... The applications of the nonstationary trap models and noise analysis techniques outlined above include noise analysis for RF circuits [15], [20], [21], [22], [23], [24], CMOS image sensors [4], [47], [6], SRAMs and DRAMs [7], [8], and phase noise analysis for oscillators [20], [27]. In Section IV, we present results obtained by the proposed models and the simulation techniques for the low frequency noise characterization of a common source amplifier and the phase jitter of a ring oscillator. ...
Defects or traps in semiconductors and nano devices that randomly capture and emit charge carriers result in low-frequency noise, such as burst and 1/f noise, that are great concerns in the design of both analog and digital circuits. The capture and emission rates of these traps are functions of the time-varying voltages across the device, resulting in nonstationary noise characteristics. Modeling of low-frequency, nonstationary noise in circuit simulators is a longstanding open problem. It has been realized that the low frequency noise models in circuit simulators were the culprits that produced erroneous noise performance results for circuits under strongly time-varying bias conditions. In this paper, we first identify an almost perfect analogy between trap noise in nano devices and the so-called ion channel noise in biological nerve cells, and propose a new approach to modeling and analysis of low-frequency noise that is founded on this connection. We derive two fully nonstationary models for traps, a fine-grained Markov chain model based on recent previous work and a completely novel coarse-grained Langevin model based on similar models for ion channels in neurons. The nonstationary trap models we derive subsume and unify all of the work that has been done recently in the device modeling and circuit design literature on modeling nonstationary trap noise. We also describe joint noise analysis paradigms for a nonlinear circuit and a number of traps. We have implemented the proposed techniques in a Matlab® based circuit simulator, by expanding the industry standard compact MOSFET model PSP to include a nonstationary description of oxide traps. We present results obtained by this extended model and the proposed simulation techniques for the low frequency noise characterization of a common source amplifier and the phase jitter of a ring oscillator.
... To cope with these errors, correlated double sampling (CDS) has proved to be an excellent solution [51]- [53], [61]. CDS is the most frequently used technique for reset noise reduction, although other schemes can be used [62]. This manuscript includes preliminary noise analysis of CDS in discrete-time current sensing we presented in [63]. ...
... We present a 124×132 imager with 20.1 μm pixels in a 0.5 μ CMOS process, capable of imaging single cell fluorescence at light levels equal to those required by cooled CCD cameras. The 5-transistor pixels feature n-well/p-sub photodiodes and a capacitive transimpedance amplifier (CTIA) for signal amplification [24] and noise reduction [25]. The novel design splits the amplifier with only nMOS transistors inside the pixels. ...
... This can manifest as an offset or a gain error. Since the active reset employed minimizes reset noise [25], the dominant temporal noise source is the read noise. ...
Traditionally, charge coupled device (CCD) based image sensors have held sway over the field of biomedical imaging. Complementary metal oxide semiconductor (CMOS) based imagers so far lack sensitivity leading to poor low-light imaging. Certain applications including our work on animal-mountable systems for imaging in awake and unrestrained rodents require the high sensitivity and image quality of CCDs and the low power consumption, flexibility and compactness of CMOS imagers. We present a 132×124 high sensitivity imager array with a 20.1 μm pixel pitch fabricated in a standard 0.5 μ CMOS process. The chip incorporates n-well/p-sub photodiodes, capacitive transimpedance amplifier (CTIA) based in-pixel amplification, pixel scanners and delta differencing circuits. The 5-transistor all-nMOS pixel interfaces with peripheral pMOS transistors for column-parallel CTIA. At 70 fps, the array has a minimum detectable signal of 4 nW/cm(2) at a wavelength of 450 nm while consuming 718 μA from a 3.3 V supply. Peak signal to noise ratio (SNR) was 44 dB at an incident intensity of 1 μW/cm(2). Implementing 4×4 binning allowed the frame rate to be increased to 675 fps. Alternately, sensitivity could be increased to detect about 0.8 nW/cm(2) while maintaining 70 fps. The chip was used to image single cell fluorescence at 28 fps with an average SNR of 32 dB. For comparison, a cooled CCD camera imaged the same cell at 20 fps with an average SNR of 33.2 dB under the same illumination while consuming over a watt.
... So reset noise is often called kT =C noise as well. Equation (3) indicates that the reset noise is independent of its resistance. Figure 4 shows the principle of the proposed reset noise reduction through column-level feedback reset operation. ...
A low reset noise CMOS image sensor (CIS) based on column-level feedback reset is proposed. A feedback loop was formed through an amplifier and a switch. A prototype CMOS image sensor was developed with a 0.18 μm CIS process. Through matching the noise bandwidth and the bandwidth of the amplifier, with the falling time period of the reset impulse 6 μs, experimental results show the reset noise level can experience up to 25 dB reduction. The proposed CMOS image sensor meets the demand of applications in high speed security surveillance systems, especially in low illumination.
... During charging, the capacitor is connected to an electron reservoir at temperature T, via a voltage-controlled switch, but after charging (standardization), it is isolated. It is well known, from the Johnson-Nyquist theorem, that the voltage uncertainty V n at completion of the standardization (reset noise [13] ...
Reduced power dissipation relative to the field-effect transistor (FET) is a key attribute that should be possessed by any device that has a chance of supplanting the FET as the ubiquitous building block for complex digital logic. We outline the possible physical approaches to achieving this attribute, and illustrate these approaches by citing current exploratory device research. We assess the value of the key exploratory research objectives of the semiconductor industry-sponsored Nanoelectronics Research Initiative (NRI) in the light of this pressing need to reduce dissipation in future digital logic devices.
