• Title/Summary/Keyword: gaussian function

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ON STATIONARY GAUSSIAN SECOND ORDER MARKOV PROCESSES

  • Park, W.J.;Hsu, Y.S.
    • Kyungpook Mathematical Journal
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    • v.19 no.2
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    • pp.249-255
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    • 1979
  • In this paper we give a characterization of Stationary Gaussian 2nd order Markov processes in terms of its covariance function $R({\tau})=E[X(t)X(t+{\tau})]$ and also give some relationship among quasi-Markov, Markov and 2nd order Markov processes.

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Flexible Nonlinear Learning for Source Separation

  • Park, Seung-Jin
    • Journal of KIEE
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    • v.10 no.1
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    • pp.7-15
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    • 2000
  • Source separation is a statistical method, the goal of which is to separate the linear instantaneous mixtures of statistically independent sources without resorting to any prior knowledge. This paper addresses a source separation algorithm which is able to separate the mixtures of sub- and super-Gaussian sources. The nonlinear function in the proposed algorithm is derived from the generalized Gaussian distribution that is a set of distributions parameterized by a real positive number (Gaussian exponent). Based on the relationship between the kurtosis and the Gaussian exponent, we present a simple and efficient way of selecting proper nonlinear functions for source separation. Useful behavior of the proposed method is demonstrated by computer simulations.

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Review of Spatial Linear Mixed Models for Non-Gaussian Outcomes (공간적 상관관계가 존재하는 이산형 자료를 위한 일반화된 공간선형 모형 개관)

  • Park, Jincheol
    • The Korean Journal of Applied Statistics
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    • v.28 no.2
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    • pp.353-360
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    • 2015
  • Various statistical models have been proposed over the last decade for spatially correlated Gaussian outcomes. The spatial linear mixed model (SLMM), which incorporates a spatial effect as a random component to the linear model, is the one of the most widely used approaches in various application contexts. Employing link functions, SLMM can be naturally extended to spatial generalized linear mixed model for non-Gaussian outcomes (SGLMM). We review popular SGLMMs on non-Gaussian spatial outcomes and demonstrate their applications with available public data.

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.

Subthreshold Characteristics of Double Gate MOSFET for Gaussian Function Distribution (가우스함수의 형태에 따른 DGMOSFET의 문턱전압이하특성)

  • Jung, Hak-Kee;Han, Ji-Hyung;Lee, Jong-In;Kwon, Oh-Shin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.05a
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    • pp.716-718
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    • 2012
  • This paper have presented the change for subthreshold characteristics for double gate(DG) MOSFET based on scaling theory and the shape of Gaussian function. To obtain the analytical solution of Poisson's equation, Gaussian function been used as carrier distribution and consequently potential distributions have been analyzed closely for experimental results, and the subthreshold characteristics have been analyzed for the shape parameters of Gaussian function such as projected range and standard projected deviation. Since this potential model has been verified in the previous papers, we have used this model to analyze the subthreshold chatacteristics. The scaling theory is to sustain constant outputs for the change of device parameters. As a result to apply the scaling theory for DGMOSFET, we know the subthreshold characteristics have been greatly changed, and the change of threshold voltage is bigger relatively.

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Small Target Detection using Morphology and Gaussian Distance Function in Infrared Images (적외선 영상에서 모폴로지와 가우시안 거리함수를 이용한 소형표적 검출)

  • Park, Jun-Jae;Ahn, Sang-Ho;Kim, Jong-Ho;Kim, Sang-Kyoon
    • Journal of Korea Society of Industrial Information Systems
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    • v.17 no.4
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    • pp.61-70
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    • 2012
  • We propose a method that finds candidate targets based on morphology and detects a small target from them using modified gaussian distance function. The existing small target detection methods use predictive filters or morphology. The methods using predictive filters take long to approach least errors. The methods using morphology are weak at clutters and need to consider size of a small target when selecting size of structure elements. We propose a robust method for small target detection to complete the existing methods. First, the proposed method deletes clutters using a median filter. Next, it does closing and opening operation using various size of structure elements, and figures target candidate pixels with subtraction operation between the results of closing and opening operation. It detects an exact small target using a gaussian distance function from the candidates target areas. The proposed method is less sensitive to clutters, and shows a detection rate of 98%.

A Linear System Approach to Serving Gaussian Traffic in Packet-Switching Networks (패킷 교환망에서 가우스 분포 트래픽을 서비스하는 선형 시스템 접근법)

  • Chong, Song;Shin, Min-Su;Chong, Hyun-Hee
    • Journal of KIISE:Information Networking
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    • v.29 no.5
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    • pp.553-561
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    • 2002
  • We present a novel service discipline, called linear service discipline, to serve multiple QoS queues sharing a resource and analyze its properties. The linear server makes the output traffic and the queueing dynamics of individual queues as a linear function of its input traffic. In particular, if input traffic is Gaussian, the distributions of queue length and output traffic are also Gaussian with their mean and variance being a function of input mean and input power spectrum (equivalently, autocorrelation function of input). Important QoS measures including buffer overflow probability and queueing delay distribution are also expressed as a function of input mean and input power spectrum. This study explores a new direction for network-wide traffic management based on linear system theories by letting us view the queueing process at each node as a linear filter.

Analysis of Subthreshold Swing for Double Gate MOSFET Using Gaussian Function (가우스함수를 이용한 DGMOSFET의 문턱전압이하 스윙분석)

  • Jung, Hak-Kee;Han, Ji-Hyung;Lee, Jae-Hyung;Jeong, Dong-Soo;Lee, Jong-In;Kwon, Oh-Shin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2011.05a
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    • pp.681-684
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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 subthreshold swing has been investigated according to projected range and standard projected deviation, variables of Gaussian function. The analytical potential distribution model has been derived from Poisson's equation, and subthreshold swing has been obtained from this model. The subthreshold swing has been defined as the derivative of gate voltage to drain current and is theoretically minimum of 60mS/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 subthreshold swings have been analyzed according to the shape of Gaussian function.

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Breakdown Voltages Deviation for Channel Dimension of Double Gate MOSFET (이중게이트 MOSFET의 채널구조에 따른 항복전압 변화)

  • Jung, Hakkee
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.3
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    • pp.672-677
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    • 2013
  • This paper have analyzed the change of breakdown voltage for channel dimension of double gate(DG) MOSFET. The breakdown voltage to have the small value among the short channel effects of DGMOSFET to be next-generation devices have to be precisely analyzed. The analytical solution of Poisson's equation have been used to analyze the breakdown voltage, and Gaussian function been used as carrier distribution to analyze closely for experimental results. The breakdown voltages have been analyzed for device parameters such as channel thickness and doping concentration, and projected range and standard projected deviation of Gaussian function. Since this potential model has been verified in the previous papers, we have used this model to analyze the breakdown voltage. As a result, we know the breakdown voltage is influenced on Gaussian function and device parameters for DGMOSFET.

Analysis of Breakdown Voltages Deviation for Channel Dimension of Double Gate MOSFET (DGMOSFET의 채널구조에 따른 항복전압변화에 대한 분석)

  • Jung, Hakkee;Han, Jihyung;Jeong, Dongsoo;Lee, Jongin
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2012.10a
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    • pp.811-814
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    • 2012
  • This paper have analyzed the change of breakdown voltage for channel dimension of double gate(DG) MOSFET. The breakdown voltage to have the small value among the short channel effects of DGMOSFET to be next-generation devices have to be precisely analyzed. The analytical solution of Poisson's equation have been used to analyze the breakdown voltage, and Gaussian function been used as carrier distribution to analyze closely for experimental results. The breakdown voltages have been analyzed for device parameters such as channel thickness and doping concentration, and projected range and standard projected deviation of Gaussian function. Since this potential model has been verified in the previous papers, we have used this model to analyze the breakdown voltage. Resultly, we know the breakdown voltage is influenced on Gaussian function and device parameters for DGMOSFET.

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