• Title/Summary/Keyword: coefficient-based method

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A Practical Method of Prediction of Resistance for Displacement Vessels

  • Doctors, Lawrence J.
    • Journal of Ship and Ocean Technology
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    • v.1 no.2
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    • pp.1-10
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    • 1997
  • The prediction of the total resistance of a ship is generally based on considering it to be a simple sum of the viscous resistance and the wave resistance. An experimental approach for predicting full-size ship resistance on this basis is practical but obviously has the deficiency that a model has to be built for each prototype of interest and the resulting tank tests are time consuming. On the other hand, purely theoretical calculations of the wave resistance, using, for example, the Michell theory, require relatively little computer time and give an excellent portrayal of the overall variation of the vessel resistance as a function of forward speed. Unfortunately, there are sufficient differences between this theory and the measured results to make this method impractical for design purposes. The proposal examined here is to use a data bank of experimental resistance results to modify the theoretical predictions. It is demonstrated that the technique will produce remarkably accurate resistance predictions and can take into account the effects of the water depth, any restriction of canal or river width, as well as the prismatic coefficient, and other geometric parameters.

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Robust Controller Design of Nuclear Power Reactor by Parametric Method

  • Yoon-Joon Lee;Man-Gyun Na
    • Nuclear Engineering and Technology
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    • v.34 no.5
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    • pp.436-444
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    • 2002
  • The robust controller for the nuclear reactor power control system is designed. Since the reactor model is not exact, it is necessary to design the robust controller that can work in the real situations of perturbations. The reactor model is described in the form of transfer function and the bound of each coefficient is determined to set up the linear interval system. By the Kharitonov and the edge theorem, a frequency based design template is made and applied to the determination of the controller. The controller designed by this method is simpler than that obtained by the H$_{\infty}$. Although the controller is designed with the basis of high power, it could be used even at low power.n at low power.

A Joint Transform Correlator Encryption System Based on Binary Encoding for Grayscale Images

  • Peng, Kaifei;Shen, Xueju;Huang, Fuyu;He, Xuan
    • Current Optics and Photonics
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    • v.3 no.6
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    • pp.548-554
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    • 2019
  • A binary encoding method for grayscale images is proposed to address their unsatisfactory decryption results from joint transform correlator (JTC) encryption systems. The method converts the encryption and decryption of grayscale images into that of binary images, and effectively improves decrypted-image quality. In the simulation, we replaced unencoded grayscale images with their binary encoded counterparts in the JTC encryption and decryption processes, then adopted a median filter to suppress saturation noise while keeping other settings unchanged. Accordingly, decrypted-image quality was clearly enhanced as the correlation coefficient (CC) between a decrypted image and its original rose from 0.8237 to 0.9473 initially, and then further to 0.9937, following the above two steps respectively. Finally, optical experimental results confirmed that the proposed encryption system works correctly.

STATISTICAL NOISE BAND REMOVAL FOR SURFACE CLUSTERING OF HYPERSPECTRAL DATA

  • Huan, Nguyen Van;Kim, Hak-Il
    • Proceedings of the KSRS Conference
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    • 2008.10a
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    • pp.111-114
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    • 2008
  • The existence of noise bands may deform the typical shape of the spectrum, making the accuracy of clustering degraded. This paper proposes a statistical approach to remove noise bands in hyperspectral data using the correlation coefficient of bands as an indicator. Considering each band as a random variable, two adjacent signal bands in hyperspectral data are highly correlative. On the contrary, existence of a noise band will produce a low correlation. For clustering, the unsupervised ${\kappa}$-nearest neighbor clustering method is implemented in accordance with three well-accepted spectral matching measures, namely ED, SAM and SID. Furthermore, this paper proposes a hierarchical scheme of combining those measures. Finally, a separability assessment based on the between-class and the within-class scatter matrices is followed to evaluate the applicability of the proposed noise band removal method. Also, the paper brings out a comparison for spectral matching measures.

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A Unit Root Test for Multivariate Autoregressive Model with Multiple Unit Roots

  • Shin, Key-Il
    • Journal of the Korean Statistical Society
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    • v.26 no.3
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    • pp.397-405
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    • 1997
  • Recently maximum likelihood estimators using unconditional likelihood function are used for testing unit roots. When one wants to use this method the determinant term of initial values in the multivariate unconditional likelihood function produces a complicated function of the elements in the coefficient matrix and variance matrix. In this paper an approximation of the determinant term is calculated and based on this aproximation an approximated unconditional likelihood function is calculated. The approximated unconditional maximum likelihood estimators can be used to test for unit roots. When multivariate process has one unit root the limiting distribution obtained by this method and the limiting distribution using exact unconditional likelihood function are the same.

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Hierarchical Optimal Control of Non-linear Systems using Fast Walsh Transform (FWT를 이용한 비선형계의 계층별 최적제어)

  • Jeong, Je-Uk;Jo, Yeong-Ho;Im, Guk-Hyeon;An, Du-Su
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.8
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    • pp.415-422
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    • 2000
  • This paper presents a new algorithm for hierarchical optimal control of nonlinear systems. The proposed method is simple because the solutions are obtained by only exchanging informations of coefficient vector based on interaction prediction principle and FWT(fast Walsh transform) in upper and lower level. Since we solve two point boundary problem with Picard's iterative method and the backward integral operational matrix of Walsh function to obtain the optimal vector of each independent subsystem, the algorithm is simple and its operation is fast without inverse matrix and kronecker product operation. In simulation, the proposed algorithm's usefulness is proved by comparison with the global optimal control methods.

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Implementation of Hidden Markov Model based Speech Recognition System for Teaching Autonomous Mobile Robot (자율이동로봇의 명령 교시를 위한 HMM 기반 음성인식시스템의 구현)

  • 조현수;박민규;이민철
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.281-281
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    • 2000
  • This paper presents an implementation of speech recognition system for teaching an autonomous mobile robot. The use of human speech as the teaching method provides more convenient user-interface for the mobile robot. In this study, for easily teaching the mobile robot, a study on the autonomous mobile robot with the function of speech recognition is tried. In speech recognition system, a speech recognition algorithm using HMM(Hidden Markov Model) is presented to recognize Korean word. Filter-bank analysis model is used to extract of features as the spectral analysis method. A recognized word is converted to command for the control of robot navigation.

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Bayesian Analysis for Neural Network Models

  • Chung, Younshik;Jung, Jinhyouk;Kim, Chansoo
    • Communications for Statistical Applications and Methods
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    • v.9 no.1
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    • pp.155-166
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    • 2002
  • Neural networks have been studied as a popular tool for classification and they are very flexible. Also, they are used for many applications of pattern classification and pattern recognition. This paper focuses on Bayesian approach to feed-forward neural networks with single hidden layer of units with logistic activation. In this model, we are interested in deciding the number of nodes of neural network model with p input units, one hidden layer with m hidden nodes and one output unit in Bayesian setup for fixed m. Here, we use the latent variable into the prior of the coefficient regression, and we introduce the 'sequential step' which is based on the idea of the data augmentation by Tanner and Wong(1787). The MCMC method(Gibbs sampler and Metropolish algorithm) can be used to overcome the complicated Bayesian computation. Finally, a proposed method is applied to a simulated data.

An Analysis of the Effects of Turbo-tape Drip Irrigation System on Chinese Cabbage (Turbo-tape을 이용한 배추의 점적관개 효과분석)

  • 정상옥
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.35 no.4
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    • pp.31-38
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    • 1993
  • For efficient irrigation of structured horiculture and upland crops, a new technique of drip irrigation using the turbo-tape for Autumn Chinese cabbage was developed. The turbo-tape worked well, and based on this study The following results were obtained ; 1. The emission uniformity of the turbo-tape was very good with a uniformity coefficient of 92.5%. 2. Starting point of irrigation at 80% of the wilting point was better than at the wilting point itself. 3. The irrigation amounts for the Autumn Chinese cabbage cultured ranged 315 to 470mm depending upon the irrigation methods, turbo-tape irrigation method could conserve irrigation water about 37% compared to the furrow irrigation method. 4. Average yields were 2, 430g when the starting point of irrigation was at the wilting point, while 2, 680g when it was at 80% of the wilting point.

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Prediction of Density Distribution in Sintered Metal Powder Compacts by Indentation Force Equation (압흔하중식에 의한 금속소결분말체내에서의 밀도분포 예측)

  • 박종진
    • Journal of Powder Materials
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    • v.4 no.3
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    • pp.188-195
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    • 1997
  • In most of sintered metal powder compacts, the sintered density distribution is controlled to be as high and uniform as possible to ensure the required mechanical properties. In general, the density distribution in the compacts is not uniform and not easy to measure. In the present study, a method for measuring the density distribution was developed, based on the indentation force equation by which the hardness and the relative density were related. The indentation force equation, expressed as a function of strength constant, workhardening coefficient and relative density, was obtained by finite element analysis of rigid-ball indentation on sintered powder metal compacts. The present method was verified by comparing the predicted density distribution in the sintered Fe-0.5%C-2%Cu compacts with that obtained by experiments, in which the density distribution was directly measured by machining the compacts from the outer surface progressively.

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