• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.606-613
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• 2003

As a technical method for controlling chaotic dynamics, this paper presents a predictive control for chaotic systems based on radial basis function networks(RBFNs). To control the chaotic systems, we employ an on-line identification unit and a nonlinear feedback controller, where the RBFN identifier is based on a suitable NARMA real-time modeling method and the controller is predictive control scheme. In our design method, the identifier and controller are most conveniently implemented using a gradient-descent procedure that represents a generalization of the least mean square(LMS) algorithm. Also, we introduce a projection matrix to determine the control input, which decreases the control performance function very rapidly. And the effectiveness and feasibility of the proposed control method is demonstrated with application to the continuous-time and discrete-time chaotic nonlinear system.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.2
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• pp.65-75
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• 2004

This paper presents a generalized predictive control method based on a fuzzy neural network(FNN) model, which uses the on-line multi-step prediction, fur the intelligent control of chaotic nonlinear systems whose mathematical models are unknown. In our design method, the parameters of both predictor and controller are tuned by a simple gradient descent scheme, and the weight parameters of FNN are determined adaptively during the operation of the system. In order to design a generalized predictive controller effectively, this paper describes computing procedure for each of the two important parameters. Also, we introduce a projection matrix to determine the control input, which deceases the control performance function very rapidly. Finally, in order to evaluate the performance of our controller, the proposed method is applied to the Doffing and Henon systems, which are two representative continuous-time and discrete-time chaotic nonlinear systems, res reactively.

• Journal of Korean Academy of Oral and Maxillofacial Radiology
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• v.28 no.2
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• pp.339-353
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• 1998

The purpose of this study was to investigate whether a radiographic estimate of osseous fractal dimension and power spectrum of 2D discrete Fourier transform is useful in the characterization of structural changes in bone. Ten specimens of bone were decalcified in fresh 50 ml solutions of 0.1 N hydrochloric acid solution at cummulative timed periods of 0 and 90 minutes. and radiographed from 0 degree projection angle controlled by intraoral parelleling device. I performed one-dimensional variance. fractal analysis of bony profiles and 2D discrete Fourier transform. The results of this study indicate that variance and fractal dimension of scan line pixel intensities decreased significantly in decalcified groups but Fourier spectral analysis didn't discriminate well between control and decalcified specimens.

• East Asian mathematical journal
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• v.32 no.1
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• pp.101-115
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• 2016

In this paper, we consider a semi-discrete mixed discontinuous Galerkin method with an interior penalty to approximate the solution of parabolic problems. We define an auxiliary projection to analyze the error estimate and obtain optimal error estimates in $L^{\infty}(L^2)$ for the primary variable u, optimal error estimates in $L^2(L^2)$ for ut, and suboptimal error estimates in $L^{\infty}(L^2)$ for the flux variable ${\sigma}$.

• East Asian mathematical journal
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• v.26 no.5
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• pp.615-626
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• 2010

In this paper, we analyze discontinuous Galerkin methods with penalty terms, namly symmetric interior penalty Galerkin methods, to solve nonlinear parabolic equations. We construct finite element spaces on which we develop fully discrete approximations using extrapolated Crank-Nicolson method. We adopt an appropriate elliptic-type projection, which leads to optimal ${\ell}^{\infty}$ ($L^2$) error estimates of discontinuous Galerkin approximations in both spatial direction and temporal direction.

• Journal of the Korean Institute of Intelligent Systems
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• v.9 no.4
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• pp.444-450
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• 1999

This paper deals with several methods: the clustering method that uses k-means algorithm to abstract the area of characters on the image document and the distance function that suits for the HIS coordinate system to cluster the image. For the prepossessing step to recognize this, or the method of characters segmentate, the algorithm to abstract a discrete character is also proposed, using the linking picture element. This algorithm provides the feature that separates any character such as the touching or overlapped character. The methods of projecting and tracking the edge have so far been used to segment them. However, with the new method proposed here, the picture element extracts a discrete character with only one-time projection after abstracting the character string. it is possible to pull out it. dividing the area into the character and the rest (non-character). This has great significance in terms of processing color documents, not the simple binary image, and already received verification that it is more advanced than the previous document processing system.

• The Journal of the Acoustical Society of Korea
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• v.38 no.5
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• pp.522-533
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• 2019

The compressive sensing model for range-Doppler estimation can be expressed as an under-determined linear system y = Ax. To find the solution of the linear system with the compressive sensing method, matrix A should be sufficiently incoherent and x to be sparse. In this paper, we propose a transmission waveform design method that maintains the bandwidth required by the sonar system while lowering the mutual coherence of the matrix A so that the matrix A is incoherent. The proposed method combines two methods of optimizing the sensing matrix with the alternating projection and suppressing unwanted frequency bands using the DFT (Discrete Fourier Transform) matrix. We compare range-Doppler estimation performance of existing waveform LFM(Linear Frequency Modulated) and designed waveform using the matched filter and the compressive sensing method. Simulation shows that the designed transmission waveform has better detection performance than the existing waveform LFM.

• Journal of radiological science and technology
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• v.37 no.4
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• pp.323-330
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• 2014

Image reconstruction is one of the most important processes in CT (Computed tomography) technology. For fast scanning and low dose to the objects, iterative reconstruction is becoming more and more important. In the implementation of iterative reconstruction, projection and backprojection processes are considered to be indispensable parts. However, many approaches for projection and backprojection may result severe image artifacts due to their discrete characteristics and affects the reconstructed image quality. Thus, new approaches for projection and backprojection are highly demanded these days. In this paper, distance-driven approach was evaluated and compared with other conventional methods. The numerical simulator was developed to make the phantoms, and projection and backprojection images were compared using these approaches. As a result, it turned out that there are less artifacts during projection and backprojection in parallel and fan beam geometry.

• Korean Chemical Engineering Research
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• v.48 no.4
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• pp.475-482
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• 2010

In this work, soft sensor based on image anlaysis is proposed for quantitatively estimating the visual appearance of manufactured products and is applied to quality monitoring. The methodology consists of three steps; (1) textural feature extraction from product images using wavelet transform, (2) numerical estimation of the product appearance through projection of the textural features on subspace, and (3) use of latent variables of textural features (i.e., numerical estimates of product appearance). The focus of this approach is on the consistent and quantitative estimation of continuous variations in visual appearance rather than on classification into discrete classes. This approach is illustrated through the application to the estimation and monitoring of the appearance of engineered stone countertops.

• The KIPS Transactions:PartD
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• v.17D no.6
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• pp.463-470
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• 2010

We presented a very fast and robust method of text line segmentation based on the DCT blocks of color image without decompression and binary transformation processes. Using DC and another three primary AC coefficients from block DCT we created a gray-scale image having reduced size by 8x8. In order to detect and locate white strips between text lines we analyzed horizontal and vertical projection profiles of the image and we applied a direct markov model to recover the missing white strips by estimating hidden periodicity. We presented performance results. The results showed that our method was 40 - 100 times faster than traditional method.