• 제목/요약/키워드: inverse Gaussian

검색결과 111건 처리시간 0.019초

Time Reversa1 Reconstruction of Ultrasonic Waves in Anisotropic Media

  • Jeong, Hyun-Jo
    • 비파괴검사학회지
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    • 제28권1호
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    • pp.54-58
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    • 2008
  • Time reversal (TR) of body waves in fluids and isotropic solids has been used in many applications including ultrasonic NDE. However, the study of the TR method for anisotropic materials is not well established. In this paper, the full reconstruction of the input signal is investigated for anisotropic media using an analytical formulation, called a modular Gaussian beam (MGB) model. The time reversal operation of this model in the frequency domain is done by taking the complex conjugate of the Gaussian amplitude and phase received at the TR mirror position. A narrowband reference signal having a particular frequency and number of cycles is then multiplied and the whole signal is inverse Fourier transformed. The original input signal is seen to be fully restored by the TR process of MGB model and this model can be more generalized to simulate the spatial and temporal focusing effects due to TR process in anisotropic materials.

On Testing Multisample Sphericity in the Complex Case

  • Nagar, D.K.;Gupta, A.K.
    • Journal of the Korean Statistical Society
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    • 제13권2호
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    • pp.73-80
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    • 1984
  • In this paper, likelihood-ratio test has been derived for testing multisample sphericity in complex multivariate Gaussian populations. The $h^{th}$ moment of the test statistic is given and its exact distribution has been derived using inverse Mellin transform. Asymptotic distribution of the statistic is also given.

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Lane Detection Based on Inverse Perspective Transformation and Kalman Filter

  • Huang, Yingping;Li, Yangwei;Hu, Xing;Ci, Wenyan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권2호
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    • pp.643-661
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    • 2018
  • This paper proposes a novel algorithm for lane detection based on inverse perspective transformation and Kalman filter. A simple inverse perspective transformation method is presented to remove perspective effects and generate a top-view image. This method does not need to obtain the internal and external parameters of the camera. The Gaussian kernel function is used to convolute the image to highlight the lane lines, and then an iterative threshold method is used to segment the image. A searching method is applied in the top-view image obtained from the inverse perspective transformation to determine the lane points and their positions. Combining with feature voting mechanism, the detected lane points are fitted as a straight line. Kalman filter is then applied to optimize and track the lane lines and improve the detection robustness. The experimental results show that the proposed method works well in various road conditions and meet the real-time requirements.

퍼지 보상기와 자기구성 신경회로망을 이용한 매니퓰레이터의 역기구학 해에 관한 연구 (A Study on the Soiution of Inverse Kinematic of Manipulator using Self-Organizing Neural Network and Fuzzy Compensator)

  • 김동희;이수흠;신위재
    • 융합신호처리학회논문지
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    • 제2권3호
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    • pp.79-85
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    • 2001
  • 본 논문에서는 퍼지 보상기와 자기구성 신경회로망을 이용하여 3축 매니퓰레이터의 역 기구학 해를 구하는 방법을 제안한다. 가우시안 위치 함수를 활성화 함수로 사용하는 자기구성 신경회로망은 학습 시작시 1개의 은닉층 노드를 가지고 학습을 하면서 점차적으로 은닉층의 노드수를 증가시킴으로서 최적의 노드수를 얻을 수 있으며, 퍼지 보상기는 신경회로망의 양호한 학습비를 얻는다. 이와 같이 시스템을 구성하여 빠른 학습속도와 학습비의 개선 그리고 빠른 정상상태로의 수렴을 확인하였다.

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수중 잔향음 신호 모의 (Simulation of underwater reverberation signals)

  • 오선택;나정열
    • 한국음향학회지
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    • 제13권6호
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    • pp.66-74
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    • 1994
  • 잔향음이 우세한 환경하에서 소나 시스템의 성능을 평가할 때 대부분의 음향 모델인 음압 준위(power level) 모델에 비해 수중 잔향음 신호 모의 모델은 매우 유용하게 이용된다. 본 논문에서는 소나 시험에 필요한 잔향음 신호(reverberation time series)를 모의하였다. 우선 주파수 영역에서 밴드의 폭이 변하고 가우시안 분포(Gaussian distribution)를 갖는 표준화된 스펙트럼(normalized spectrum)을 수신 시간 간격에 따라 구하였다. 두번째로, 기존의 음향 모델의 결과인 시간에 따른 잔향음 준위를 각각의 표준화된 스펙트럼의 준위와 합성하였다. 마지막으로 음원 신호의 스펙트럼과 잔향음 스펙트럼을 곱(product)하고 이 결과를 역푸리에 변환(inverse Fourier transform)을 이용하여 신호를 모의하였다.

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Novel Partitioning Algorithm for a Gaussian Inverse Wishart PHD Filter for Extended Target Tracking

  • Li, Peng;Ge, Hongwei;Yang, Jinlong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제11권11호
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    • pp.5491-5505
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    • 2017
  • Use of the Gaussian inverse Wishart PHD (GIW-PHD) filter has demonstrated promise as an approach to track an unknown number of extended targets. However, the partitioning approaches used in the GIW-PHD filter, such as distance partition with sub-partition (DP-SP), prediction partition (PP) and expectation maximization partition (EMP), fails to provided accurate partition results when targets are spaced closely together and performing maneuvers. In order to improve the performance of a GIW-PHD filter, this paper presents a cooperation partitioning (CP) algorithm to solve the partitioning issue when targets are spaced closely together. In the GIW-PHD filter, the DP-SP is insensitive to target maneuvers but sensitive to the differences in target sizes, while EMP is the opposite. The proposed CP algorithm is a fusion approach of DP-SP and EMP, which employs EMP as a sub-partition approach after DP. Therefore, the CP algorithm will be sensitive to neither target maneuvers nor differences in target sizes. The simulation results show that the use of the proposed CP algorithm will improve the performance of the GIW-PHD filter when targets are spaced closely together.

예산 제약과 예약 정책이 있는 복수 제품 신문 배달 소년 문제 해결을 위한 효율적 방법론 (An Efficient Method for Solving a Multi-Item Newsboy Problem with a Budget-Constraint and a Reservation Policy)

  • 이창용
    • 산업경영시스템학회지
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    • 제37권1호
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    • pp.50-59
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    • 2014
  • In this paper, we develop an efficient approach to solve a multiple-item budget-constraint newsboy problem with a reservation policy. A conventional approach for solving such problem utilizes an approximation for the evaluation of an inverse of a Gaussian cumulative density function when the argument of the function is small, and a heuristic method for finding an optimal Lagrangian multiplier. In contrast to the conventional approach, this paper proposes more accurate method of evaluating the function by using the normalization and an effective numerical integration method. We also propose an efficient way to find an optimal Lagrangian multiplier by proving that the equation for the budget-constraint is in fact a monotonically increasing function in the Lagrangian multiplier. Numerical examples are tested to show the performance of the proposed approach with emphases on the behaviors of the inverse of a Gaussian cumulative density function and the Lagrangian multiplier. By using sensitivity analysis of different budget constraints, we show that the reservation policy indeed provides greater expected profit than the classical model of not having the reservation policy.

Value at Risk of portfolios using copulas

  • Byun, Kiwoong;Song, Seongjoo
    • Communications for Statistical Applications and Methods
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    • 제28권1호
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    • pp.59-79
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    • 2021
  • Value at Risk (VaR) is one of the most common risk management tools in finance. Since a portfolio of several assets, rather than one asset portfolio, is advantageous in the risk diversification for investment, VaR for a portfolio of two or more assets is often used. In such cases, multivariate distributions of asset returns are considered to calculate VaR of the corresponding portfolio. Copulas are one way of generating a multivariate distribution by identifying the dependence structure of asset returns while allowing many different marginal distributions. However, they are used mainly for bivariate distributions and are not widely used in modeling joint distributions for many variables in finance. In this study, we would like to examine the performance of various copulas for high dimensional data and several different dependence structures. This paper compares copulas such as elliptical, vine, and hierarchical copulas in computing the VaR of portfolios to find appropriate copula functions in various dependence structures among asset return distributions. In the simulation studies under various dependence structures and real data analysis, the hierarchical Clayton copula shows the best performance in the VaR calculation using four assets. For marginal distributions of single asset returns, normal inverse Gaussian distribution was used to model asset return distributions, which are generally high-peaked and heavy-tailed.

A Probabilistic Interpretation of the KL Spectrum

  • Seongbaek Yi;Park, Byoung-Seon
    • Journal of the Korean Statistical Society
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    • 제29권1호
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    • pp.1-8
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    • 2000
  • A spectrum minimizing the frequency-domain Kullback-Leibler information number has been proposed and used to modify a spectrum estimate. Some numerical examples have illustrated the KL spectrum estimate is superior to the initial estimate, i.e., the autocovariances obtained by the inverse Fourier transformation of the KL spectrum estimate are closer to the sample autocovariances of the given observations than those of the initial spectrum estimate. Also, it has been shown that a Gaussian autoregressive process associated with the KL spectrum is the closest in the timedomain Kullback-Leibler sense to a Gaussian white noise process subject to given autocovariance constraints. In this paper a corresponding conditional probability theorem is presented, which gives another rationale to the KL spectrum.

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4-구륜 2-자유도 이동 로보트의 기구학 모델과 가우스함수를 이용한 경로설계 및 추적 알고리즘 (Kinematic model, path planning and tracking algorithms of 4-wheeled mobile robot 2-degree of freedom using gaussian function)

  • 김기열;정용국;박종국
    • 전자공학회논문지S
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    • 제34S권12호
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    • pp.19-29
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    • 1997
  • This paper presents stable kinematic modeling and path planning and path tracking algorithms for the poisition control of 4-wheeled 2-d.o.f(degree of freedom) mobile robot. We drived the actuated inverse and sensed forward solution for the calculation of actuator velocity and robot velocities. the deal-reckoning algorithm is introduced to calculate the position of WMR in real time. The gaussian functions are applied to control and to design the smooth orientation angle of WMR and the path planning algorithm for obstacle avoidance is prosed. We composed feedback control system to compensate for error because of uncertainty kinematic modeling and measurement noise. The simulation resutls show that the proposed kinematkc modeling and path planning and feedback control algorithms are useful.

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