• Title/Summary/Keyword: Gaussian distribution function

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Analysis of Drain Induced Barrier Lowering for Double Gate MOSFET Using Gaussian Distribution (가우스분포를 이용한 이중게이트 MOSFET의 드레인유기장벽감소 분석)

  • Jung, Hak-Kee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.2
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    • pp.325-330
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    • 2012
  • In this paper, drain induced barrier lowering(DIBL) has been analyzed as one of short channel effects occurred in double gate(DG) MOSFET to be next-generation devices. Since Gaussian function been used as carrier distribution for solving Poisson's equation to obtain analytical solution of potential distribution, we expect our results using this model agree with experimental results. DIBL has been investigated according to projected range and standard projected deviation as variables of Gaussian function, and channel structure and channel doping intensity as device parameter. Since the validity of this analytical potential distribution model derived from Poisson's equation has already been proved in previous papers, DIBL has been analyzed using this model. Resultly, DIBL has been greatly changed for channel structure and doping concentration.

Noncentral F-Distribution for an M-ary Phase Shift Keying Wedge-Shaped Region

  • Kim, Jung-Su;Chong, Jong-Wha
    • ETRI Journal
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    • v.31 no.3
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    • pp.345-347
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    • 2009
  • This letter presents an alternative analytical expression for computing the probability of an M-ary phase shift keying (MPSK) wedge-shaped region in an additive white Gaussian noise channel. The expression is represented by the cumulative distribution function of known noncentral F-distribution. Computer simulation results demonstrate the validity of our analytical expression for the exact computation of the symbol error probability of an MPSK system with phase error.

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Analysis of Subthreshold Swing for Oxide Thickness and Doping Distribution in DGMOSFET (산화막두께 및 도핑분포에 대한 DGMOSFET의 문턱전압이하 스윙분석)

  • Jung, Hak-Kee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.15 no.10
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    • pp.2217-2222
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    • 2011
  • In this paper, the relationship of potential and charge distribution in channel for double gate(DG) MOSFET has been derived from Poisson's equation using Gaussian function. The relationship of subthreshold swing and oxide thickness has been investigated according to variables of doping distribution using Gaussian function, i.e. projected range and standard projected deviation, The analytical potential distribution model has been derived from Poisson's equation, and subthreshold swing has been obtained from this model for the change of oxide thickness. The subthreshold swing has been defined as the derivative of gate voltage to drain current and is theoretically minimum of 60 mS/dec, and very important factor in digital application. Those results of this potential model are compared with those of numerical simulation to verify this model. As a result, since potential model presented in this paper is good agreement with numerical model, the relationship of subthreshold swing and oxide thickness have been analyzed according to the shape of doping distribution.

Identification of the Distribution Function of the Preisach Model using Inverse Algorithm

  • Koh, Chang-Seop;Ryu, Jae-Seop
    • KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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    • v.2B no.4
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    • pp.168-173
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    • 2002
  • A new identification algorithm for the Preisach model is presented. The algorithm treats the identification procedure of the Preisach model as an inverse problem where the independent variables are parameters of the distribution function and the objective function is constructed using only the initial magnetization curve or only tile major loop of the hysteresis curve as well as the whole reversal curves. To parameterize the distribution function, the Bezier spline and Gaussian function are used for the coercive and interaction fields axes, respectively. The presented algorithm is applied to the ferrite permanent magnets, and the distribution functions are correctly found from the major loop of the hysteresis curve or the initial magnetization curve.

Prediction of Performance Loss Due to Phase Noise in Digital Satellite Communication System (디지털 위성통신시스템에서 위상 잡음으로 인한 성능 손실 예측)

  • 김영완;박동철
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.13 no.7
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    • pp.679-686
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    • 2002
  • Based on the alternating series expansion of error probability function due to phase noise in PSK systems, the performance evaluations for Tikhonov and Gaussian probability density functions were performed in this paper. The range of the signal-to-noise ratio of recovered carrier signal which provides the same dependency between the error performances by Tikhonov function and Gaussian function was analyzed via loss evaluation due to phase noise. The phase noise with 1/f$^2$ characteristic was generated based on the relationship of the phase noise spectral density and the modulation index for frequency modulation signal. Using the generated phase noise as the input signal for digital satellite communication receiver, the performance losses due to the phase noise were measured and evaluated with the analyzed performance characteristics.

The ex-Gaussian analysis of reaction time distributions for cognitive experiments (ex-Gaussian 모형을 활용한 인지적 과제의 반응시간 분포 분석)

  • Park, Hyung-Bum;Hyun, Joo-Seok
    • Science of Emotion and Sensibility
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    • v.17 no.2
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    • pp.63-76
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    • 2014
  • Although most behavioral reaction times (RTs) for cognitive tasks exhibit positively skewed distributions, the majority of studies primarily rely on a measure of central tendency (e.g. mean) which can cause misinterpretations of data's underlying property. The purpose of current study is to introduce procedures for describing characteristics of RT distributions, thereby effectively examine the influence of experimental manipulations. On the basis of assumption that RT distribution can be represented as a convolution of Gaussian and exponential variables, we fitted the ex-Gaussian function under a maximum-likelihood method. The ex-Gaussian function provides quantitative parameters of distributional properties and the probability density functions. Here we exemplified distributional analysis by using empirical RT data from two conventional visual search tasks, and attempted theoretical interpretation for setsize effect leading proportional mean RT delays. We believe that distributional RT analysis with a mathematical function beyond the central tendency estimates could provide insights into various theoretical and individual difference studies.

Multilevel Threshold Selection Method Based on Gaussian-Type Finite Mixture Distributions (가우시안형 유한 혼합 분포에 기반한 다중 임계값 결정법)

  • Seo, Suk-T.;Lee, In-K.;Jeong, Hye-C.;Kwon, Soon-H.
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.6
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    • pp.725-730
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    • 2007
  • Gray-level histogram-based threshold selection methods such as Otsu's method, Huang and Wang's method, and etc. have been widely used for the threshold selection in image processing. They are simple and effective, but take too much time to determine the optimal multilevel threshold values as the number of thresholds are increased. In this paper, we measure correlation between gray-levels by using the Gaussian function and define a Gaussian-type finite mixture distribution which is combination of the Gaussian distribution function with the gray-level histogram, and propose a fast and effective threshold selection method using it. We show the effectiveness of the proposed through experimental results applied it to three images and the efficiency though comparison of the computational complexity of the proposed with that of Otsu's method.

Error Rate for the Limiting Poisson-power Function Distribution

  • Joo-Hwan Kim
    • Communications for Statistical Applications and Methods
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    • v.3 no.1
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    • pp.243-255
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    • 1996
  • The number of neutron signals from a neutral particle beam(NPB) at the detector, without any errors, obeys Poisson distribution, Under two assumptions that NPB scattering distribution and aiming errors have a circular Gaussian distribution respectively, an exact probability distribution of signals becomes a Poisson-power function distribution. In this paper, we show that the error rate in simple hypothesis testing for the limiting Poisson-power function distribution is not zero. That is, the limit of ${\alpha}+{\beta}$ is zero when Poisson parameter$\kappa\rightarro\infty$, but this limit is not zero (i.e., $\rho\ell$>0)for the Poisson-power function distribution. We also give optimal decision algorithms for a specified error rate.

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Adaptable Center Detection of a Laser Line with a Normalization Approach using Hessian-matrix Eigenvalues

  • Xu, Guan;Sun, Lina;Li, Xiaotao;Su, Jian;Hao, Zhaobing;Lu, Xue
    • Journal of the Optical Society of Korea
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    • v.18 no.4
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    • pp.317-329
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    • 2014
  • In vision measurement systems based on structured light, the key point of detection precision is to determine accurately the central position of the projected laser line in the image. The purpose of this research is to extract laser line centers based on a decision function generated to distinguish the real centers from candidate points with a high recognition rate. First, preprocessing of an image adopting a difference image method is conducted to realize image segmentation of the laser line. Second, the feature points in an integral pixel level are selected as the initiating light line centers by the eigenvalues of the Hessian matrix. Third, according to the light intensity distribution of a laser line obeying a Gaussian distribution in transverse section and a constant distribution in longitudinal section, a normalized model of Hessian matrix eigenvalues for the candidate centers of the laser line is presented to balance reasonably the two eigenvalues that indicate the variation tendencies of the second-order partial derivatives of the Gaussian function and constant function, respectively. The proposed model integrates a Gaussian recognition function and a sinusoidal recognition function. The Gaussian recognition function estimates the characteristic that one eigenvalue approaches zero, and enhances the sensitivity of the decision function to that characteristic, which corresponds to the longitudinal direction of the laser line. The sinusoidal recognition function evaluates the feature that the other eigenvalue is negative with a large absolute value, making the decision function more sensitive to that feature, which is related to the transverse direction of the laser line. In the proposed model the decision function is weighted for higher values to the real centers synthetically, considering the properties in the longitudinal and transverse directions of the laser line. Moreover, this method provides a decision value from 0 to 1 for arbitrary candidate centers, which yields a normalized measure for different laser lines in different images. The normalized results of pixels close to 1 are determined to be the real centers by progressive scanning of the image columns. Finally, the zero point of a second-order Taylor expansion in the eigenvector's direction is employed to refine further the extraction results of the central points at the subpixel level. The experimental results show that the method based on this normalization model accurately extracts the coordinates of laser line centers and obtains a higher recognition rate in two group experiments.

Analysis of Subthreshold Current Deviation for Channel Dimension of Double Gate MOSFET (이중게이트 MOSFET의 채널 크기에 따른 문턱전압이하 전류 변화 분석)

  • Jung, Hakkee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.18 no.1
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    • pp.123-128
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    • 2014
  • This paper analyzed the change of subthreshold current for channel dimension of double gate(DG) MOSFET. The nano-structured DGMOSFET to reduce the short channel effect had to be preciously analyze. Poisson's equation had been used to analyze the potential distribution in channel, and Gaussian function had been used as carrier distribution. The subthreshold current had been analyzed for device parameters such as channel dimension, and projected range and standard projected deviation of Gaussian function. Since this potential model was verified in the previous papers, we used this model to analyze the subthreshold current. Resultly, we know the subthreshold current was influenced on parameters of Gaussian function and channel dimension for DGMOSFET.