• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.980-983
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• 1996

A new version of the discrete-time optimal FIR (finite impulse response) filter utilizing only the measurements of finite sliding estimation window is suggested for linear time-invariant state-space models. This filter is called the BLUFIR (best linear unbiased finite impulse response) filter since it provides the BLUE (best linear unbiased estimate) of the state obtained from the measurements of the estimation window. It is shown that the BLUFIR filter has the deadbeat property when there are no noises in the estimation window.

• Communications of the Korean Mathematical Society
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• v.20 no.4
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• pp.685-693
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• 2005

An aperiodic perfect map(APM) is an array with the property that every array of certain size, called a window, arises exactly once as a contiguous subarray in the array. In this article, we deal with the generalization of APM in higher dimensional arrays. First, we reframe all known definitions onto the generalized n-dimensional arrays. Next, some elementary known results on arrays are generalized to propositions on n-dimensional arrays. Finally, with some devised integer representations, two constructions of infinite family of n-dimensional APMs are generalized from known 2-dimensional constructions in [7].

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.7
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• pp.1437-1446
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• 2012

In this paper we propose a new stereo matching algorithm which is suitable for application to obtain depth information with high-speed in stereoscopic camera environment. For satisfying these condition we propose a new adaptive stereo matching technique using frequency information in discrete wavelet (DWT) domain and variable matching window. The size of the matching window is selected by analysis of the local property of the image in spatial domain and the feature and scaling factor of the matching window is selected by the frequency property in the frequency domain. For using frequency information we use local DWT and global DWT. We identified that the proposed technique has better peak noise to signal ratio (PSNR) than the fixed matching techniques with similar complexity.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.580-583
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• 2007

Various matching methods have been introduced by investigators to improve digital elevation model (DEM) accuracy of satellite imagery. This study proposed an area-based matching method according to land cover property using correlation coefficient of pixel brightness value between the two images for DEM generation from IKONOS stereo imagery. For this, matching line (where "matching line" implies straight line that is approximated to complex nonlinear epipolar geometry) is established by exterior orientation parameters to minimize search area. The matching is carried out based on this line. Land cover classes are divided off into water, urban land, forest and agricultural land. Matching size is selected using a correlation-coefficient image in the four areas. The selected sizes are $81{\times}81$ pixels window, $21{\times}21$ pixels window, $119{\times}119$ pixels window and $51{\times}51$ pixels window in the water area, urban land, forest land and agricultural land, respectively. And hence, DEM is generated from IKONOS stereo imagery using the selected matching sizes and land cover map on the four types.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.6_2
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• pp.587-597
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• 2007

This study determines matching size for digital elevation model (DEM) production according to land cover property from IKONOS Geo-level stereo image. We applied area based matching method using correlation coefficient of pixel brightness value between the two images. After matching line (where "matching line" implies straight line that is approximated to complex non-linear epipolar geometry) is established by exterior orientation parameters to minimize search area, the matching is carried out based on this line. The experiment is performed according to land cover property, which is divided off into four areas (water, urban land, forest land and agricultural land). In each of the test areas, matching size is selected using a correlation-coefficient image and parallax image. As the results, optimum matching size of the images was selected as $81{\times}81$ pixels window, $21{\times}21$ pixels window, $119{\times}119$ pixels window and $51{\times}51$ pixels window in the water area, urban land, forest land and agricultural land, respectively.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.7 no.4
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• pp.285-294
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• 2007

In this paper, we investigate a novel online estimation algorithm for dynamic Bayesian network(DBN) parameters, given as conditional probabilities. We sequentially update the parameter adjustment rule based on observation data. We apply our algorithm to two well known representations of DBNs: to a first-order Markov Chain(MC) model and to a Hidden Markov Model(HMM). A sliding window allows efficient adaptive computation in real time. We also examine the stochastic convergence and stability of the learning algorithm.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.153-160
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• 2009

In relation to digital elevation model(DEM) production using high resolution satellite imagery, existing studies present that DEM accuracy differently show according to land cover property. This study therefore proposes auto-selection method of window size for correlation matching according to land cover property of IKONOS Geo-level stereo image. For this, land cover classified image is obtained by IKONOS color image with four bands. In addition, correlation-coefficients are computed at regular intervals in pixels of the window-search area to shorten of matching time. As the results, DEM by the proposed method showed more accurate than DEM using the fixed window-size matching. We estimate that accuracy of the proposed DEM improved more than DEM by digital map and ERDAS in agricultural land.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.344-347
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• 2004

Critical cryptography applications require the production of an unpredictable and unbiased stream of binary data derived from a fundamental noise mechanism. In this paper, we proposed a RNG with Gaussian noise using filter algorithm. The proposed scheme is designed to reduce the statistical property of the biased bit stream in the output of a RNG. Experimental show that we analysis the loss rate according to window size and propose optimum window size.

• Proceedings of the Korean Society For Composite Materials Conference
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• 2004.10a
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• pp.232-235
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• 2004

This is the preliminary study to develop composite window frame of commercial aircraft using VaRTM process. For two candidate carbon fabric(triaxial fabric, sleeving braider dry carbon fiber), specimens were fabricated using VaRTM process ,and then the physical & mechanical tests were performed to gain material property according to ASTM. FEM analysis for each candidate carbon fabric were performed to find the minimum ply number and weight for composite window frame. In this study Tsai-Wu strength failure criteria was utilized to evaluate the safety of structure.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.47 no.1
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• pp.97-102
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• 2010

A laser speckle is a random pattern that has a granular appearance produced by reflected light when a coherent laser illuminates an irregular course surface. Most important property of laser speckle is detecting micro-vascular. Speckle image needs image processing to detect micro-vascular. This paper proposes a new image processing method for laser speckle, adaptive window method that adaptively processes laser speckle images in the spatial. Conventional fixed window based LASCA has shortcoming in that it uses the same window size regardless of target areas. Inherently laser speckle contains undesired noise. Thus a large window is helpful for removing the noise but it results in low resolution of image. Otherwise a small window may detect micro vascular but it has limits in noise removal. To overcome this trade-off, we newly introduce the concept of adaptive window method to conventional laser speckle image analysis. We have compared conventional LASCA and its variants with the proposed method in terms of image quality and processing complexity.