Modeling random telegraph signal noise in CMOS image sensor under low light based on binomial distribution

The random telegraph signal noise in the pixel source follower MOSFET is the principle component of the noise in the CMOS image sensor under low light. In this paper, the physical and statistical model of the random telegraph signal noise in the pixel source follower based on the binomial distribution is set up. The number of electrons captured or released by the oxide traps in the unit time is described as the random variables which obey the binomial distribution. As a result,the output states and the corresponding probabilities of the first and the second samples of the correlated double sampling circuit are acquired. The standard deviation of the output states after the correlated double sampling circuit can be obtained accordingly. In the simulation section, one hundred thousand samples of the source follower MOSFET have been simulated,and the simulation results show that the proposed model has the similar statistical characteristics with the existing models under the effect of the channel length and the density of the oxide trap. Moreover, the noise histogram of the proposed model has been evaluated at different environmental temperatures.

Distributed Signal Condition System for EAST Tokamak

In order to achieve both the signal condition remote control and the work statute self-check through Ethernet,a distributed signal condition (DSC) system has been developed for control and data acquisition (CODAC) in the EAST tokamak nuclear fusion experiment.Based on differential amplifiers,analog multiplexers and the embedded Ethernet communication technology,a DSC system is designed and produced.This paper summarizes the DSC system design,and presents a kind of calibration method for it.This DSC system has been integrated into the EAST CODAC system,and used successfully in the 2008 EAST experiments.The user-friendly,high performance,and cost-effective DSC system greatly improves the work efficiency and reduces the fault rates of the CODAC system.

A Two-Layer Fuzzy Control Strategy for the Participation of Energy Storage Battery Systems in Grid Frequency Regulation

To address the frequency fluctuation problem caused by the power dynamic imbalance between the power system and the loadwhen a large number of newenergy sources are connected to the grid,a two-layer fuzzy control strategy is proposed for the participation of the energy storage battery system in FM.Firstly,considering the coordination of FM units responding to automatic power generation control commands,a comprehensive allocation strategy of two signals under automatic power generation control commands is proposed to give full play to the advantages of two FM signals while enabling better coordination of two FM units responding to FM commands;secondly,based on the grid FM demand and battery FM capability,a double-layer fuzzy control strategy is proposed for FM units responding to automatic power generation control commands in a coordinated manner under dual-signal allocation mode to precisely allocate the power output depth of FM units,which can control the fluctuation of frequency deviation within a smaller range at a faster speed while maintaining the battery charge state;finally,the proposed Finally,the proposed control strategy is simulated and verified inMatlab/Simulink.The results show that the proposed control strategy can control the frequency deviation within a smaller range in a shorter time,better stabilize the fluctuation of the battery charge level,and improve the utilization of the FM unit.

Investigation of L1_0 FePt-based soft/hard composite bit-patterned media by micromagnetic simulation

The soft/hard composite patterned media have potential to be the next generation of magnetic recording, but the composing modes of soft and hard materials have not been investigated systematically. L10 FePt-based soft/hard composite patterned media with an anisotropic constant distribution are studied by micromagnetic simulation. Square arrays and hexagonal arrays with various pitch sizes are simulated for two composing types： the soft layer that encloses the hard dots and the soft layer that covers the whole surface. It is found that the soft material can reduce the switching fields of bits effectively for all models. Compared with the first type, the second type of models possess low switching fields, narrow switching field distributions, and high gain factors due to the introduction of inter-bit exchange coupling. Furthermore, the readout waveforms of the second type are not deteriorated by the inter-bit soft layers. Since the recording density of hexagonal arrays are higher than that of square arrays with the same center-to-center distances, the readout waveforrns of hexagonal arrays are a little worse, although other simulation results are similar for these two arrays.

Design and implementation of the NaI(Tl)/CsI(Na) detectors output signal generator

We designed and implemented a signal generator that can simulate the output of the NaI（Tl）/CsI（Na）detectors＇pre-amplifier onboard the Hard X-ray Modulation Telescope（HXMT）.Using the development of the FPGA（Field Programmable Gate Array）with VHDL language and adding a random constituent,we have finally produced the double exponential random pulse signal generator.The statistical distribution of the signal amplitude is programmable.The occurrence time intervals of the adjacent signals contain negative exponential distribution statistically.

High-Sensitivity Transcriptome Data Structure and Implications for Analysis and Biologic Interpretation

Novel microarray technologies such as the AB1700 platform from Applied Biosysterns promise significant increases in the signal dynamic range and a higher sensitivity for weakly expressed transcripts. We have compared a representative set of AB1700 data with a similarly representative Affymetrix HG-U133A dataset. The AB1700 design extends the signal dynamic detection range at the lower bound by one order of magnitude. The lognormal signal distribution profiles of these highsensitivity data need to be represented by two independent distributions. The additional second distribution covers those transcripts that would have gone undetected using the Affymetrix technology. The signal-dependent variance distribution in the AB1700 data is a non-trivial function of signal intensity, describable using a composite function. The drastically different structure of these highsensitivity transcriptome profiles requires adaptation or even redevelopment of the standard microarray analysis methods. Based on the statistical properties, we have derived a signal variance distribution model for AB1700 data that is necessary for such development. Interestingly, the dual lognormal distribution observed in the AB1700 data reflects two fundamentally different biologic mechanisms of transcription initiation.

Generation of Synthetic Transcriptome Data with Defined Statistical Properties for the Development and Testing of New Analysis Methods

We have previously developed a combined signal/variance distribution model that accounts for the particular statistical properties of datasets generated on the Applied Biosystems AB1700 transcriptome system. Here we show that this model can be efficiently used to generate synthetic datasets with statistical properties virtually identical to those of the actual data by aid of the JAVA application ace.map creator 1.0 that we have developed. The fundamentally different structure of AB1700 transcriptome profiles requires re-evaluation, adaptation, or even redevelopment of many of the standard microarray analysis methods in order to avoid misinterpretation of the data on the one hand, and to draw full benefit from their increased specificity and sensitivity on the other hand. Our composite data model and the ace.map creator 1.0 application thereby not only present proof of the correctness of our parameter estimation, but also provide a tool for the generation of synthetic test data that will be useful for further development and testing of analysis methods.

Distributed Estimation in Sensor Networks with Repetition Coding

This paper considers the distributed estimation of a source parameter using quantized sensor observations in a wireless sensor network with noisy channels. Repetition codes are used to transmit quantization bits of sensor observations and a quasi best linear unbiased estimate is constructed to estimate the source parameter. Simulations show that the estimation scheme achieves a better power and spectral efficiency than the previous scheme.

Universal Distributed Estimation Scheme for a Bandwidth Constrained Ad Hoc Sensor Network

This paper describes a distributed estimation scheme （DES） for a bandwidth constrained ad hoc sensor network. The DES is universal in the sense that operations on all sensors are identical and independent of noise distribution. The scheme requires each sensor to transmit just a 1-bit message per observation. Simulation results show that the scheme achieves much better mean-squares error （MSE） performance than the simplified isotropic universal DES and even outperforms the isotropic universal DES which requires more than twice the bandwidth of this scheme.

Distributed Estimation for Sensor Networks with Channel Estimation Errors

This paper describes the effect of channel estimation error （CEE） on the performance of distributed estimations of an unknown parameter in a wireless sensor network. Both the classical and Bayesian estimators are derived to mitigate the adverse effects caused by the CEE. Power scheduling among sensors and the power ratio between the training and data transmission at each individual node are optimized by directly minimizing the final average mean squared error to compensate for the CEE. A closed-form power scheduling policy is given for a homogeneous environment, which shows that more than 50% of the power should be allocated to sensor observation transmissions. For an inhomogeneous environment, a multilevel waterfilling type solution is developed for the power scheduling among sensors for only the sum power constraint with a ＂cave＂ waterfilling solution for both the sum and individual power constraints. Simulations show that the proposed power scheduling schemes achieve better performance than the equal power scheduling scheme.

Simple,High-Performance Fusion Rule for Censored Decisions in Wireless Sensor Networks

Data selection-based summation fusion （DSSF） was developed to overcome the shortcomings ot previously developed likelihood ratio tests based on channel statistics （LRT-CS） for the problem of fusing censored binary decisions transmitted over Nakagami fading channels in a wireless sensor network （WSN）. The LRT-CS relies on detection probabilities of the local sensors, while the detection probabilities are a priori unknown for uncooperative targets. Also, for Nakagami fading channels, the LRT-CS involves an infinite series, which is cumbersome for real-time application. In contrast, the DSSF only involves data comparisons and additions and does not require the detection probabilities of local sensors. Furthermore, the performance of DSSF is only slightly degraded in comparison with the LRT-CS when the detection probabilities of local sensors are a priori unknown. Therefore, the DSSF should be used in a WSN with limited resources.

Distributed and Decentralized Control Architectures for Converter-Interfaced Microgrids

This paper gives a summary on recently available technologies for decentralized and distributed control of microgrids.They can be classified into two general categories:1)power line communication based architectures and 2)multi-agent based architectures.The essential control methods and information sharing algorithms applied in these architectures are reviewed and examined in a hierarchical manner,in order to point out benefits they will bring to future microgrid applications.The paper is concluded with a summary on existing methods and a discussion on future development trends.