• 제목/요약/키워드: High order statistics

검색결과 551건 처리시간 0.046초

국부 통계 특성을 이용한 적응 MAP 방식의 고해상도 영상 복원 방식 (Adaptive MAP High-Resolution Image Reconstruction Algorithm Using Local Statistics)

  • 김경호;송원선;홍민철
    • 한국통신학회논문지
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    • 제31권12C호
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    • pp.1194-1200
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    • 2006
  • 본 논문에서는 국부 통계 특성을 이용한 적응 MAP 방식의 고해상도 영상 복원 알고리즘에 대해 제안한다. 고해상도 원 영상의 윤곽선을 보존하기 위해 저해상도 영상의 국부 특성을 이용하여 시각함수를 정의하였고, MAP(Maximum A Posteriori) 추정 방식을 이용하여 국부적인 열화 정도(smoothness)를 조절하였다. 또한 가중치가 부여된 함수를 이용하여 원 고해상도 영상에 가능한 가까운 최적의 해를 찾기 위하여 반복기법을 사용하였으며, 열화 요소는 매 반복 단계마다 부분적으로 복원된 고해상도 영상으로부터 이용하였다. 제안된 방식의 성능을 실험 결과를 통해 확인할 수 있었다.

Analysis on the Interactions of Harmonics in Exhaust Pipes of Automotive Engines

  • Lee, Min-Ho;Lee, Joon-Seo;Cha, Kyung-Ok
    • Journal of Mechanical Science and Technology
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    • 제17권12호
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    • pp.1867-1875
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    • 2003
  • In exhaust pipes of automotive engines, the pulsating pressure waves are composed of fundamental frequency and high order harmonics. The nonlinearities in the exhaust pipe is caused by their interactions. The error between prediction and measurement is induced by the nonlinearities. We can not explain this phenomenon using linear acoustics theory. So power spectrum, which is used in linear theory, is not useful. This paper is concerned with the development of useful engineering techniques to detect and analyze nonlinearity in exhaust pipe of automotive engines. The study of higher order statistics has been dominated by work on the bispectrum. The bispectrum can be viewed as a decomposition of the third moment (skewness) of a signal over frequency and as such is blind to symmetric nonlinearities. The phenomenon of quadratic phase coupling (QPC) can be analyzed by the bicoherence function. Finally the application of these techniques to data from actual exhaust pipe systems is performed.

함수적 변동성 fGARCH(1, 1)모형을 통한 초고빈도 시계열 변동성 (The fGARCH(1, 1) as a functional volatility measure of ultra high frequency time series)

  • 윤재은;김종민;황선영
    • 응용통계연구
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    • 제31권5호
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    • pp.667-675
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    • 2018
  • 초고빈도(ultra high frequency; UHF)시계열의 함수적 변동성 측정을 위한 최신 기법인 함수적 변동성 functional GARCH : fGARCH(1, 1) 모형을 소개하고 설명하였다. 실증분석을 위해 R-code fGARCH(1, 1) 프로그램을 KOSPI/현대차 초고빈도 수익률 자료에 적합하여 예시하였다.

Designing Rich-Secure Network Covert Timing Channels Based on Nested Lattices

  • Liu, Weiwei;Liu, Guangjie;Ji, Xiaopeng;Zhai, Jiangtao;Dai, Yuewei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제13권4호
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    • pp.1866-1883
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    • 2019
  • As the youngest branch of information hiding, network covert timing channels conceal the existence of secret messages by manipulating the timing information of the overt traffic. The popular model-based framework for constructing covert timing channels always utilizes cumulative distribution function (CDF) of the inter-packet delays (IPDs) to modulate secret messages, whereas discards high-order statistics of the IPDs completely. The consequence is the vulnerability to high-order statistical tests, e.g., entropy test. In this study, a rich security model of covert timing channels is established based on IPD chains, which can be used to measure the distortion of multi-order timing statistics of a covert timing channel. To achieve rich security, we propose two types of covert timing channels based on nested lattices. The CDF of the IPDs is used to construct dot-lattice and interval-lattice for quantization, which can ensure the cell density of the lattice consistent with the joint distribution of the IPDs. Furthermore, compensative quantization and guard band strategy are employed to eliminate the regularity and enhance the robustness, respectively. Experimental results on real traffic show that the proposed schemes are rich-secure, and robust to channel interference, whereas some state-of-the-art covert timing channels cannot evade detection under the rich security model.

Multiple Group Testing Procedures for Analysis of High-Dimensional Genomic Data

  • Ko, Hyoseok;Kim, Kipoong;Sun, Hokeun
    • Genomics & Informatics
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    • 제14권4호
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    • pp.187-195
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    • 2016
  • In genetic association studies with high-dimensional genomic data, multiple group testing procedures are often required in order to identify disease/trait-related genes or genetic regions, where multiple genetic sites or variants are located within the same gene or genetic region. However, statistical testing procedures based on an individual test suffer from multiple testing issues such as the control of family-wise error rate and dependent tests. Moreover, detecting only a few of genes associated with a phenotype outcome among tens of thousands of genes is of main interest in genetic association studies. In this reason regularization procedures, where a phenotype outcome regresses on all genomic markers and then regression coefficients are estimated based on a penalized likelihood, have been considered as a good alternative approach to analysis of high-dimensional genomic data. But, selection performance of regularization procedures has been rarely compared with that of statistical group testing procedures. In this article, we performed extensive simulation studies where commonly used group testing procedures such as principal component analysis, Hotelling's $T^2$ test, and permutation test are compared with group lasso (least absolute selection and shrinkage operator) in terms of true positive selection. Also, we applied all methods considered in simulation studies to identify genes associated with ovarian cancer from over 20,000 genetic sites generated from Illumina Infinium HumanMethylation27K Beadchip. We found a big discrepancy of selected genes between multiple group testing procedures and group lasso.

순환정상 프로세스의 고차 통계 특성을 이용한 디지털 변조인식 (Digitally Modulated Signal Classification based on Higher Order Statistics of Cyclostationary Process)

  • 안우현;나선필;서보석
    • 방송공학회논문지
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    • 제19권2호
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    • pp.195-204
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    • 2014
  • 이 논문에서는 순환정상 프로세스의 고차 통계 특성을 바탕으로 2-FSK, 4-FSK, 8-FSK, MSK, BPSK, QPSK, 8-PSK, 16-QAM, 32-QAM, 64-QAM 등 10개의 기저대역 디지털 변조신호를 자동으로 인식하는 방법을 제안하였다. 변조신호의 고유한 성질을 나타내는 특징변수로는 1차 순환 모멘트와 고차 순환 큐뮬런트를 이용하였다. 제안한 변조인식기는 크게 두 단계로 구성되며, 첫 번째 단계에서는 1차 순환 모멘트가 나타내는 첨두치를 이용하여 M-FSK와 비FSK로 변조신호를 분류한다. 두 번째 단계에서는 비FSK를 분류하기 위해 고차 순환 큐뮬런트 값을 이용하는 Gaussian 혼합 모델 기반의 분류기를 적용하였다. 제안한 방법의 성능을 검증하기 위해서 모의실험을 실시하였다. 모의실험 결과 제안한 분류기는 주파수와 위상 옵셋이 존재하는 환경에서도 우수한 분류확률을 나타내었다.

실시간 고차통계 정규화와 Smoothing 필터를 이용한 강인한 음성인식 (Robust Speech Recognition Using Real-Time High Order Statistics Normalization and Smoothing Filter)

  • 정주현;송화전;김형순
    • 대한음성학회:학술대회논문집
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    • 대한음성학회 2005년도 춘계 학술대회 발표논문집
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    • pp.91-94
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    • 2005
  • The performance of speech recognition is degraded by the mismatch between training and test environments. Many methods have been presented to compensate for additive noise and channel effect in the cepstral domain, and Cepstral Mean Subtraction (CMS) is the representative method among them. Recently, high order cepstral moment normalization method has introduced to improve recognition accuracy. In this paper, we apply high order moment normalization method and smoothing filter for real-time processing. In experiments using Aurora2 DB, we obtained error rate reduction of 49.7% with the proposed algorithm in comparison with baseline system.

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JADE알고리즘의 개선에 관한 연구 (A Study on the Improvement of the JADE Algorithm)

  • 윤형로;이진술;전대근;이경중
    • 대한전기학회논문지:시스템및제어부문D
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    • 제52권5호
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    • pp.305-310
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    • 2003
  • In this paper, we proposed an IJADE(Improved joint approximate diagonalisation of eigenmatrices) which use high order statistics instead of second order statistics for data whitening. For simulation, we artificially construct signals mixed with two ECG signals, 60Hz power line interference and 16Hz sine signal and then put them into a JADE and an IJADE. To evaluate the performance of separated ECG signal in each algorithm, we have adopted indices such as kurtosis, standard deviation ratio, correlation coefficient and euclidean distance. As a results, IJ ADE showed theimproved performances as kurtosis of $2\%,$ standard deviation ratio of 0.2194, and Euclidean distance of 0.07 except correlation coefficient showing similar value. In conclusion, the proposed IJADE showed a good performance in separating ECG and a possibilities in applying to the various biological signal.

자기 적응 등화를 위한 MMA와 SCA 알고리즘의 성능 비교 (The Performance Comparison of the MMA and SCA Algorithm for Self Adaptive Equalization)

  • 임승각
    • 한국인터넷방송통신학회논문지
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    • 제12권2호
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    • pp.159-165
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    • 2012
  • 본 논문에서는 통신 채널에서 발생되는 찌그러짐과 잡음의 영향을 최소화하기 위하여 사용되는 적응 등화 알고리즘인 MMA (Multi-Modulus Algorithm)와 SCA (Square Contour Algorithm)의 성능을 비교하였다. 송신 신호는 통신 채널의 진폭 전달 특성과 위상 전달 특성의 비선형성으로 인하여 찌그러져 수신될 것이므로 수신측에서 자기 적응 등화 방식을 사용하여 이들을 보상하는 것이 필요하게 된다. 자기 적응 등화 알고리즘에서는 Constant Modulus가 중요한 의미를 가지는데, 이의 계산을 위하여 MMA는 송신 신호의 2차와 4차 의 고차 통계치를 이용하지만 SCA는 2차 통계치만을 이용하는 Modulus를 이용하게 된다. 다른 알고리즘에 비해 간단한 연산으로 이들 2 가지의 전달 특성을 동시에 보상할 수 있는 알고리즘인 MMA와 SCA의 성능을 컴퓨터 시뮬레이션을 통해 비교하였다. 이때 성능의 비교를 위하여 필수적인 복원 성상도, 잔류 isi양 및 MSE, SER을 사용하였으며, 성능의 비교 결과 송신 신호의 고차 통계치를 이용하는 MMA 방식이 MSE, SER,에서 저차 통계치를 이용하는 SCA 방식보다 우월하였으며 복원 성상도와 잔류 isi에서는 SCA가 MMA보다 우월함을 알 수 있었다.

Bayesian Estimation of Multinomial and Poisson Parameters Under Starshaped Restriction

  • Oh, Myong-Sik
    • Communications for Statistical Applications and Methods
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    • 제4권1호
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    • pp.185-191
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    • 1997
  • Bayesian estimation of multinomial and Poisson parameters under starshped restriction is considered. Most Bayesian estimations in order restricted statistical inference require the high-dimensional integration which is very difficult to evaluate. Monte Carlo integration and Gibbs sampling are among alternative methods. The Bayesian estimation considered in this paper requires only evaluation of incomplete beta functions which are extensively tabulated.

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