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This paper presents a power-efficient 10-bit SAR ADC. A novel comparator topology with a dynamic common-gate stage is proposed to increase the pre-amplification gain under a low power supply voltage, thereby reducing noise and offset. Statistical estimation and loading switching techniques are synergically combined to further improve the energy efficiency. Moreover, the SAR sequencer and clock generator...
Traversable region estimation is the fundamental enabler in autonomous navigation. In this paper, we propose a traversable region segmentation algorithm using stereo vision. We address this problem mainly in road scenes for the goal of autonomous driving. Using only geometry information, our approach has the advantages of effectiveness and robustness. The proposed approach is based on a cascaded framework...
This paper presents a power-efficient noise reduction technique for successive approximation register analog-to-digital converters (ADCs) based on the statistical estimation theory. It suppresses both comparator noise and quantization error by accurately estimating the ADC conversion residue. It allows a high signal-to-noise ratio (SNR) to be achieved with a noisy low-power comparator and a relatively...
Among the models that describe the dynamic behaviors of financial market, the discrete time microstructure model stands out because of its efficiency in considering the relationship between the price, excess demand, and liquidity of a market. However, the estimation problem of such a microstructure model is challenging, because the model is essentially a nonlinear state space model. A decent solution...
This paper presents a power-efficient SNR enhancement technique for SAR ADCs. By accurately estimating the conversion residue, it can suppress both comparator noise and quantization error. Thus, it allows the use of a noisy low-power comparator and a relatively low resolution DAC to achieve high resolution. The proposed technique has low hardware complexity, requiring no change to the standard ADC...
A Bayesian Network was proposed to estimate human body posture in three dimensional using a probabilistic inference way. In this study, to represent and reconstruct the motion of human body, a three dimensional rigid links model which consists of bones and joints was built. Belief Propagation algorithm was employed to implement Bayesian probabilistic inference for the estimation task. Based on the...
Pulse transit time (PTT) has shown a high correlation with blood pressure and have been reported to be used for blood pressure estimation. However, PTT based blood pressure estimation is not accurate yet, especially for diastolic blood pressure estimation. In this study, we introduced a new compensation method for PTT based blood pressure estimation. A liner model for PTT based blood pressure estimation...
The maximum tire road friction coefficient greatly affect the dynamic vehicle response under defined driving conditions, which makes it a crucial parameter to vehicle dynamics control and active safety systems. A maximum road friction estimation scheme was proposed in this paper, in which the instantaneous tire friction was obtained by analyzing the vehicle dynamics response, and a new transient frictionwheel...
In consideration the drawbacks of some existing road adhesion coefficient estimation methods, a maximum road friction estimation method was proposed in this paper based on the model reconstruction principles, which fully took the advantages that the wheel dynamic parameters of distributed drive electric vehicle can be obtained accurately. The simplified tire model originated from magic formula for...
Estimation of the tire-road friction using the signal of on-board sensors is very important for the vehicle dynamic control systems. This paper presented a tire -- Croad friction coefficient estimation algorithm based on a modified Dugoff model. The proposed algorithm first determined the tire slip ratio and the instantaneous longitudinal friction coefficient using vehicle and wheel dynamics parameters...
This paper presents a novel approach to detect traffic congestion on roads in a natural open world scene observed from TV cameras placed on poles or buildings. In this system, a time-spatial imagery based algorithm is proposed to estimate the road status from the video. The experimental results on real road traffic congestion estimation show that the time-spatial method is robust in complex lighting...
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