• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1711-1714
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• 2003

The noise in an image degrades image quality and deteriorates coding efficiency of compression. Recently, various edge-preserving noise filtering methods based on the nonstationary image model have been proposed to overcome this problem. In most conventional nonstationary image models, however, pixels are assumed to be uncorrelated to each other In order not to increase the computational burden too much. As a result, some detailed information is lost in the filtered results. In this paper, we propose a computationally feasible adaptive noise smoothing algorithm which considers the nonstationary correlation characteristics of images. We assume that an image has a nonstationary mean and can be segmented into subimages which have individually different stationary correlations. Taking advantage of the special structure of the covariance matrix that results from the proposed image model, we derive a computationally efficient FFT-based adaptive linear minimum mean square error filter. The justification for the proposed image model is presented and the effectiveness of the proposed algorithm is demonstrated experimentally.

• Journal of Korea Water Resources Association
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• v.31 no.4
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• pp.363-373
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• 1998

In this study, random flow field in a nonstationary porous formation is characterized through cross covariances of the velocity with the log conductivity and the head. The hydraulic head and the velocity in saturated aquifers are found through stochastic analysis of a steady, two-dimensional flow field without recharge. Expression for these cross covariances are obtained in quasi-analytic forms all in terms of the parameters which characterize the nonstationary conductivity field and the average head gradient. The cross covariances with a Gaussian correlation function for the log conductivity are presented for two particular cases where the trend is either parallel or perpendicular to the mean head gradient and for separation distances along and across the mean flow direction. The results may be of particular importance in transport predictions and conditioning on field measurements when the log conductivity field is suspected to be nonstationary and also serve as a benchmark for testing nonstationary numerical codes. Keywords : cross covariance, nonstationary conductivity field, saturated aquifer, stochastic analysis.

• Wind and Structures
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• v.38 no.1
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• pp.1-13
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• 2024

In order to effectively simulate nonstationary stochastic turbulent wind fields, four separation hybrid (SEP-H) models are proposed in the present study. Based on the assumption that the lateral turbulence component at one single-point is uncorrelated with the longitudinal and vertical turbulence components, the fluctuating wind is separated into 2nV-1D and nV1D nonstationary stochastic vector processes. The first process can be expressed as double proper orthogonal decomposition (DPOD) or proper orthogonal decomposition and spectral representation method (POD-SRM), and the second process can be expressed as POD or SRM. On this basis, four SEP-H models of nonstationary stochastic turbulent wind fields are developed. In addition, the orthogonal random variables in the SEP-H models are presented as random orthogonal functions of elementary random variables. Meanwhile, the number theoretical method (NTM) is conveniently adopted to select representative points set of the elementary random variables. The POD-FFT (Fast Fourier transform) technique is introduced in frequency to give full play to the computational efficiency of the SEP-H models. Finally, taking a long-span bridge as the engineering background, the SEP-H models are compared with the dimension-reduction DPOD (DR-DPOD) model to verify the effectiveness and superiority of the proposed models.

• Publications of The Korean Astronomical Society
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• v.18 no.1
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• pp.15-20
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• 2003

In the earlier papers we analyzed the axisymmetric, nonstationary electrodynamics of the central black hole and a surrounding thin accretion disk in an active galactic nucleus. Based on those papers we analyze the axisymmetric, nonstationary black hole magnetosphere in this paper. We concentrate on deriving the ‘Grad-Shafranov equations’; both in the force-free and non-force-free cases. In the time-independent limit our equations naturally coincide with stationary equations as they should.

• Publications of The Korean Astronomical Society
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• v.17 no.1
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• pp.7-10
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• 2002

In the earlier papers we analyzed the axisymmetric, nonstationary electrodynamics of the central black hole and a surrounding thin accretion disk in an active galactic nucleus. Based on those papers we analyze the axisymmetric, nonstationary force-free black hole magnetosphere and the motion of the plasma. We concentrate on deriving the relations between the velocity components of the plasma and those of the accreting magnetic field lines. We conclude that the former are given by the sum of the latter and the magnetic field terms.

• Communications for Statistical Applications and Methods
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• v.20 no.3
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• pp.207-215
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• 2013

In this paper, we implement an empirical study to test whether the time series of daily returns in stock and Won/USD exchange markets is strictly stationary or explosive. The results indicate that only a few series show nonstationary volatility when dramatic events erupted; in addition, this nonstationary behavior occurs more often in the Won/USD exchange market than in the stock market.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.289-291
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• 2002

Host of source separation methods focus on stationary sources so higher-order statistics is necessary In this paler we consider a problem of source separation when sources are second-order nonstationary stochastic processes . We employ the natural gradient method and develop learning algorithms for both 1inear feedback and feedforward neural networks. Thus our algorithms possess equivariant property Local stabi1iffy analysis shows that separating solutions are always locally stable stationary points of the proposed algorithms, regardless of probability distributions of

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1997.10a
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• pp.345-351
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• 1997

The motion of an aircraft landing gear over rough runway at variable speed is nonstationary. hi this paper, a method for the computation of nonstationary response variance is presented which uses a state space form for the combination of landing gear and runway excitation. The dynamic characteristics of the landing gear under nonstationazy random excitations has also been analyzed using the proposed method. The formulation is for linear systems of arbitrary order and allows any deterministic velocity history.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.50 no.5
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• pp.233-240
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• 2001

This paper presents a time series prediction method using a fuzzy rule-based system. Extracting fuzzy rules by performing a simple one-pass operation on the training data is quite attractive because it is easy to understand, verify, and extend. The simplest method is probably to relate an estimate, x(n+k), with past data such as x(n), x(n-1), ..x(n-m), where k and m are prefixed positive integers. The relation is represented by fuzzy if-then rules, where the past data stand for premise part and the predicted value for consequence part. However, a serious problem of the method is that it cannot handle nonstationary data whose long-term mean is varying. To cope with this, a new training method is proposed, which utilizes the difference of consecutive data in a time series. In this paper, typical previous works relating time series prediction are briefly surveyed and a new method is proposed to overcome the difficulty of prediction nonstationary data. Finally, computer simulations are illustrated to show the improved results for various time series.

• Journal of Mechanical Science and Technology
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• v.14 no.9
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• pp.968-977
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• 2000

The motion of an aircraft landing gear over a rough runway can be modeled by a nonclassically damped system subject to nonstationary random excitations. In this paper, the approximate analysis methods based on either the real or complex normal modes for the computation of nonstationary response covariances are proposed. It has been found by simulation involving a realistic example that, for the nonclassically damped random vibrational systems, the approximate solution method based on the complex normal mode is superior to other approaches with respect to the accuracy and computation time.