• Journal of the Korea Society of Computer and Information
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• v.25 no.2
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• pp.49-58
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• 2020

In this study, we solve an online multi-object problem which finds object states (i.e. locations and sizes) while conserving their identifications in online-provided images and detections. We handle this problem based on a tracking-by-detection approach by linking (or associating) detections between frames. For more accurate online association, we propose novel online appearance learning with discrete fourier transform and partial least square analysis (PLS). We first transform each object image into a Fourier image in order to extract meaningful features on a frequency domain. We then learn PLS subspaces which can discriminate frequency features of different objects. In addition, we incorporate the proposed appearance learning into the recent confidence-based association method, and extensively compare our methods with the state-of-the-art methods on MOT benchmark challenge datasets.

• Communications for Statistical Applications and Methods
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• v.16 no.3
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• pp.409-419
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• 2009

In this article, an explicit solution of the EM algorithm for the image deburring is presented. To obtain the restore image from the strictly iterative EM algorithm is quite time-consumed and impractical in particular when the underlying observed image is not small and the number of iterations required to converge is large. The explicit solution provides a quite reasonable restore image although it exploits the approximation in the outside of the valid area of image, and also allows to obtain the effective EM solutions without iteration process in real-time in practice by using the discrete finite Fourier transformation.

• Journal of Navigation and Port Research
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• v.27 no.5
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• pp.499-504
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• 2003

This paper describes the system for evaluating the sea wave informations such as wave direction and wave length in real time, by using image data obtained from the marine X-band radar. We proposed here a method for automatic selection of the partial image data without the user's individual selection at the radar. We also discussed that the wave direction could be obtained by a 2-dimensional discrete Fourier transform algorithm. We carried some evaluation works on the algorithm through computer simulation. The obtained thirteen radar image data under several sea surface conditions were analyzed by the method described and the result was presented.

• Journal of Wetlands Research
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• v.21 no.4
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• pp.365-373
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• 2019

In this study, we investigated the effect of wave height in coastal areas using discrete wavelet transform in Taehwa river basin in Ulsan. Through the decomposition result of tide data using daubechies level 7 wavelet and Curve Fitting Function, we confirmed that detail components of d₃ and d₄ were semidiurnal and diurnal components and approximation component(a₆) was the long period of lunar fortnight constituent. The decomposed tide data in six level was divided into tide component with periodicity and wave component with non-periodicity using autocorrelation function and fourier transform. Finally, we confirmed that the tide component is consisted 66% and wave component is consisted 34%. So, we quantitatively assessed the effect of wave on coastal areas. The result could be used for coastal flood risk management considering the effect of wave.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.29 no.4 s.235
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• pp.578-583
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• 2005

This paper introduces a fast Fourier transform (FFT)-based spectral dynamic analysis method for the transient responses as well as the steady-state responses of the linear discrete systems subject to non-zero initial conditions. The forced vibration of a viscously damped three-DOF system is considered as the illustrative numerical example. The proposed spectral analysis method is evaluated by comparing its results with the exact analytical solutions and the numerical solutions obtained by the Runge-Kutta method.

• Journal of the Korean Society for Railway
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• v.9 no.1 s.32
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• pp.63-68
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• 2006

This paper proposes a fast Fourier transform(FFT)-based spectral analysis method(SAM) for the dynamic responses of the linear discrete dynamic models with non-proportional damping. The SAM was developed by using discrete Fourier transform(DFT)-theory. To verify the proposed SAM, a three-DOF system with non-proportional viscous damping is considered as an illustrative example. The present SAM is evaluated by comparing the dynamic responses obtained by SAM with those obtained by Runge-Kutta method.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.24 no.8
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• pp.84-93
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• 2010

This paper describes a method of visualization and fast estimation of parameter in continuous time signal. The parameter estimation method of this paper directly estimate the parameters on the basis of the discrete Fourier transform. Also, this paper present to efficient visualization method of dominant parameters obtained in continuous time signal. The proposed methods are applied to test functions with three dominant modes. The results show that the proposed methods are highly applicable to parameter estimation and visualization in continuous time signal.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.113-118
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• 2024

In this paper, we propose an optimal wavelet in a system for canceling background noise of acoustic signals. This system performed Discrete Wavelet Transform(DWT) instead of the existing Short Time Fourier Transform(STFT) and then improved noise cancellation performance through a deep learning process. DWT functions as a multi-resolution band-pass filter and obtains transformation parameters by time-shifting the parent wavelet at each level and using several wavelets whose sizes are scaled. Here, the noise cancellation performance of several wavelets was tested to select the most suitable mother wavelet for analyzing the speech. In this study, to verify the performance of the noise cancellation system for various wavelets, a simulation program using Tensorflow and Keras libraries was created and simulation experiments were performed for the four most commonly used wavelets. As a result of the experiment, the case of using Haar or Daubechies wavelets showed the best noise cancellation performance, and the mean square error(MSE) was significantly improved compared to the case of using other wavelets.

• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.185-189
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• 2009

무선 센서 네트워크는 화산 감시, 전장 감시, 동물 서식지 감시, 건축물의 감시, 농장 관리, 의료분야등 다양한 분야에서 연구되고 있다. 국내에서도 국가 정책 사업으로 교량 및 건축물의 균열 감시, 표적의 침입 탐지 및 식별을 위한 무선 센서 네트워크 연구가 활발히 진행 중이다. 특히, 무선 센서 네트워크의 다양한 분야의 연구 중에서 철조망을 이용한 표적의 침입 탐지 및 식별에 관한 연구는 산업 시설, 보안지역, 교도소, 군사지역, 공항 등 다양한 분야에서 사용된다. 현재 철조망 감시는 대부분 유선 센서 노드를 통한 유선 센서 네트워크 환경에서 이루어지고 있다. 기존의 유선 센서 네트워크는 높은 데이터 전송률을 통해 수신되는 높은 정보의 신호를 이용하여 고속 푸리에 변환에 의한 신호의 주파수 분석 기법을 사용해 왔다. 하지만, 유선 센서 네트워크의 높은 데이터 전송률과 비교하여 무선 센서 네트워크의 센서 노드는 유선 센서 네트워크에 비해 매우 낮은 데이터 전송률을 가진다. 따라서 무선 센서 네트워크에서 수신되는 신호의 정보가 매우 낮고, 유선 센서 네트워크에서 사용된 고속 푸리에 변환에 의한 신호의 주파수 분석에 따른 주파수별 특징 추출을 할 수 없다. 따라서 본 논문에서는 철조망 감시를 위한 높은 데이터 전송률을 보장하는 유선 센서 네트워크에 비해 제한된 통신자원과 센서 노드의 낮은 데이터 전송률로 인해 수신되는 한정적인 신호의 정보를 이용한 무선 센서 네트 워크에서 철조망의 표적 침입 탐지 및 식별을 위한 특징 추출 알고리즘을 제안한다.

• Journal of The Korean Association of Information Education
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• v.15 no.3
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• pp.517-524
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• 2011

This paper presents a fast blind deconvolution method that produces a deblurring result from a single image in only a few seconds. The high speed of our method is enabled by considering the Discrete Fourier Transform (DFT), and its relation to filtering and convolution, and fast computation of Moore-Penrose inverse matrix. How can we predict the behavior of an arbitrary filter, or even more to the point design a filter to achieve certain specifications. The idea is to study the frequency response of the filter. This concept leads to an useful convolution formula. A Matlab implementation of our method usually takes less than one minute to deblur an image of moderate size, while the deblurring quality is comparable.