• Title/Summary/Keyword: threshold bootstrap

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Semi-parametric Bootstrap Confidence Intervals for High-Quantiles of Heavy-Tailed Distributions (꼬리가 두꺼운 분포의 고분위수에 대한 준모수적 붓스트랩 신뢰구간)

  • Kim, Ji-Hyun
    • Communications for Statistical Applications and Methods
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    • v.18 no.6
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    • pp.717-732
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    • 2011
  • We consider bootstrap confidence intervals for high quantiles of heavy-tailed distribution. A semi-parametric method is compared with the non-parametric and the parametric method through simulation study.

A PWM Control Strategy for Low-speed Operation of Three-level NPC Inverter based on Bootstrap Gate Drive Circuit (부트스트랩 회로를 적용한 3-레벨 NPC 인버터의 저속 운전을 위한 PWM 스위칭 전략)

  • Jung, Jun-Hyung;Ku, Hyun-Keun;Im, Won-Sang;Kim, Wook;Kim, Jang-Mok
    • The Transactions of the Korean Institute of Power Electronics
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    • v.19 no.4
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    • pp.376-382
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    • 2014
  • This paper proposes the pulse width modulation (PWM) control strategy for low-speed operation in the three-level neutral-point-clamped (NPC) inverters based on the bootstrap gate drive circuit. As a purpose of the cost reduction, several papers have paid attention to the bootstrap circuit applied to the three-level NPC inverter. However, the bootstrap gate driver IC cannot generate the gate signal to the IGBT for low-speed operation, because the bootstrap capacitor voltage decreases under the threshold level. For low-speed operation, the dipolar and partial-dipolar modulations can be the effective solution. However, these modulations have drawbacks in terms of the switching loss and THD. Therefore, this paper proposes the PWM control strategy to operate the inverter at low-speed and to minimize the switching loss and harmonics. The experimental results are presented to verify the validity on the proposed method.

Multiple-threshold asymmetric volatility models for financial time series (비대칭 금융 시계열을 위한 다중 임계점 변동성 모형)

  • Lee, Hyo Ryoung;Hwang, Sun Young
    • The Korean Journal of Applied Statistics
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    • v.35 no.3
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    • pp.347-356
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    • 2022
  • This article is concerned with asymmetric volatility models for financial time series. A generalization of standard single-threshold volatility model is discussed via multiple-threshold in which we specialize to twothreshold case for ease of presentation. An empirical illustration is made by analyzing S&P500 data from NYSE (New York Stock Exchange). For comparison measures between competing models, parametric bootstrap method is used to generate forecast distributions from which summary statistics of CP (Coverage Probability) and PE (Prediction Error) are obtained. It is demonstrated that our suggestion is useful in the field of asymmetric volatility analysis.

Confidence Intervals for High Quantiles of Heavy-Tailed Distributions (꼬리가 두꺼운 분포의 고분위수에 대한 신뢰구간)

  • Kim, Ji-Hyun
    • The Korean Journal of Applied Statistics
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    • v.27 no.3
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    • pp.461-473
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    • 2014
  • We consider condence intervals for high quantiles of heavy-tailed distribution. The asymptotic condence intervals based on the limiting distribution of estimators are considered together with bootstrap condence intervals. We can also apply a non-parametric, parametric and semi-parametric approach to each of these two kinds of condence intervals. We considered 11 condence intervals and compared their performance in actual coverage probability and the length of condence intervals. Simulation study shows that two condence intervals (the semi-parametric asymptotic condence interval and the semi-parametric bootstrap condence interval using pivotal quantity) are relatively more stable under the criterion of actual coverage probability.

A Novel Text Sample Selection Model for Scene Text Detection via Bootstrap Learning

  • Kong, Jun;Sun, Jinhua;Jiang, Min;Hou, Jian
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.13 no.2
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    • pp.771-789
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    • 2019
  • Text detection has been a popular research topic in the field of computer vision. It is difficult for prevalent text detection algorithms to avoid the dependence on datasets. To overcome this problem, we proposed a novel unsupervised text detection algorithm inspired by bootstrap learning. Firstly, the text candidate in a novel form of superpixel is proposed to improve the text recall rate by image segmentation. Secondly, we propose a unique text sample selection model (TSSM) to extract text samples from the current image and eliminate database dependency. Specifically, to improve the precision of samples, we combine maximally stable extremal regions (MSERs) and the saliency map to generate sample reference maps with a double threshold scheme. Finally, a multiple kernel boosting method is developed to generate a strong text classifier by combining multiple single kernel SVMs based on the samples selected from TSSM. Experimental results on standard datasets demonstrate that our text detection method is robust to complex backgrounds and multilingual text and shows stable performance on different standard datasets.

Study of the Simulation of VoIP Traffic Generation with Considering Self-Similiarity (자기유사성을 고려한 VoIP 트래픽 생성 시뮬레이션 방법 의 연구)

  • 김윤배;이계신;김재범
    • Proceedings of the Korea Society for Simulation Conference
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    • 2004.05a
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    • pp.25-29
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    • 2004
  • VoIP는 인터넷 프로토콜(IP)를 이용하여 음성을 데이터 packet처럼 전송하는 것을 의미한다. 최근 VoIP 기술의 도입으로 기존 망 성능 관리에 대한 관심이 높아지고 있다. 보다 원활한 기술 구현을 위해서는 VoIP 트래픽에 대한 체계적인 분석과 위험성 검증을 할 수 있는 도구가 필요하다. 또한 기존의 트래픽 시뮬레이션 기법에서 실제 망에서의 자기유사성을 적용한 사례가 적다는 것 또한 본 연구가 행하여진 동기이다. 본 연구에서는 자기유사성을 반영하여 소량의 샘플을 갖고 전체 VoIP 망 트래픽을 생성할 수 있는 방법론을 개발하고자 시도하였다.

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kNNDD-based One-Class Classification by Nonparametric Density Estimation (비모수 추정방법을 활용한 kNNDD의 이상치 탐지 기법)

  • Son, Jung-Hwan;Kim, Seoung-Bum
    • Journal of Korean Institute of Industrial Engineers
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    • v.38 no.3
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    • pp.191-197
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    • 2012
  • One-class classification (OCC) is one of the recent growing areas in data mining and pattern recognition. In the present study we examine a k-nearest neighbors data description (kNNDD) algorithm, one of the OCC algorithms widely used. In particular, we propose to use nonparametric estimation methods to determine the threshold of the kNNDD algorithm. A simulation study has been conducted to explore the characteristics of the proposed approach and compare it with the existing approach that determines the threshold. The results demonstrate the usefulness and flexibility of the proposed approach.

A Study on Nonlinear Dynamic Adjustment of Gasoline Prices in Korea (우리나라 휘발유 가격의 비선형 동적 조정에 관한 연구)

  • Park, Haesun;Lee, Sangjik
    • Environmental and Resource Economics Review
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    • v.22 no.2
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    • pp.393-410
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    • 2013
  • We employ a threshold vector error correction models (TVECM) to investigate the nonlinear dynamic adjustment of gasoline prices in Korea. We consider 10 regional gasoline markets including Seoul, Busan, Daegu, Incheon, Kwangju, Daejeon, Ulsan, Kangwon, Chungbuk, Jeonbuk and construct 9 price differences against Seoul. We use the bootstrap procedure suggested by Hansen (1999) and generalized by Lo and Zivot (2001) to show that three-regime TVECM is suitable for our analysis. Results indicate the gasoline price adjustment processes are nonlinear. Our estimation shows that Seoul-Daejeon, Seoul-Daegu and Seoul-Ulsan have bigger transaction costs than other market pairs and thus gasoline prices of these three regional markets are lower than that of Seoul. Gasoline prices of the other 6 regional markets are close to Seoul's price. One interesting finding is that the transaction costs are not proportional to geographical distances. This implies that transportation costs are not the main factor of the transaction costs. The transaction costs may depends on the competition intensity of gasoline markets in supply side.

Generation of Simulation Input Data Using Threshold Bootstrap (임계값 붓스트랩을 사용한 입력 시나리오의 생성)

  • Kim Yun-Bae;Kim Jae-Bum;Ko Jong-Suk
    • Proceedings of the Korean Operations and Management Science Society Conference
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    • 2003.05a
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    • pp.1179-1185
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    • 2003
  • 시뮬레이션 상의 입력모델에 대한 기존의 연구는 과거의 자료를 바탕으로 선형의 모수적인 (parametric) 모형을 개발하는데 초점을 두고 있다. 그러나 이 경우에는 입력이 매우 복잡한 형태를 가지면 모수적인 모형을 잦는 것이 불가능해지므로 비모수적인(non-parametric) 접근방법이 절실한 실정이다 예로 인터넷 트래픽 모델의 시뮬레이션 수행시 입력으로 제공되는 단위 시간당 요구되는 웹 페이지의 수 같은 경우 데이터들 간데 종속관계가 매우 심하고 복잡하여 모수적 모형을 세우는데 어려움이 있다. 이러한 시스템들을 시뮬레이션 방법으로 분석 하고자 할 때, 기존의 trace-driven 시뮬레이션 방법이나 모수적 모형을 찾아 다수의 사실적인 시뮬레이션 입력 자료를 확보하는 것은 현실적으로 어려움이 있다. 따라서. 비모수적인 방법으로 다수의 사실적인 시뮬레이션 입력 자료를 생성하는 것이 필요하다. 이러한 비모수적인 방법에 대한 평가기준 설정은 시뮬레이션 상의 입력 모델에 대한 타당성을 제시한다는 점에서 또한 매우 중요하다. 본 논문에서는 붓트스트 랩의 방법중의 하나인 임계값 붓트스트랩을 이용하여 시뮬레이션 입력 자료 생성 방법을 개발하였고 Turing test를 통해 붓스트랩으로 생성산 입력 시나리오를 검증하였다.

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Design of MOSFET-Controlled FED integrated with driver circuits

  • Lee, Jong-Duk;Nam, Jung-Hyun;Kim, Il-Hwan
    • Journal of Korean Vacuum Science & Technology
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    • v.3 no.1
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    • pp.66-73
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    • 1999
  • In this paper, the design of one-chip FED system integrated with driving circuits in reported on the basis of MOSFET controlled FEA (MCFEA). To integrate a MOSFET with a FEA efficiently, a new fabrication process is proposed. It is confirmed that the MOSFET with threshold voltage of about 2volts controls the FEA emission current up to 20 ${\mu}$A by applying driving voltage of 15 volts, which is enough current level to utilize the MCFEA as a pixel for FED. The drain breakdown voltage of the MOSFET is measured to be 70 volts, which is also high enough for 60 volt operation of FED. The circuits for row and column driver are designed stressing on saving area, reducing malfunction probability and consuming low power to maximize the merit of on-chip driving circuits. Dynamic logic concept and bootstrap capacitors are used to meet these requirements. By integrating the driving circuit with FEA, the number of external I/O lines can be less than 20, irrespectively of the number of pixels.

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