• Journal of the Society of Naval Architects of Korea
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• v.31 no.2
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• pp.91-98
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• 1994

An efficient optimization procedure combining the frequency approximation technique and the component-mode synthesis method is proposed for the structural dynamic optimization of the large structures subject to prescribed natural frequency constraints. Frequency constraints are approximated by using the first-order sensitivities with respect to both design parameters and their reciprocals. The component-mode synthesis method proposed by the authors in Ref.[8] is used for the repetitive detail finite-element analysis and sensitivity analysis. The validity of the proposed optimization procedure is confirmed through the numerical implementation of some examples. The presented approximation technique requires much smaller number of repetitive analysis than that using the sensitivities with respect to design parameters only, and further improvement in the numerical efficiency is achieved by the adoption of the introduced component-mode synthesis.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.1
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• pp.206-211
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• 2006

The quantification analysis problem is that how the m entities that have n characteristics can be linked to p-dimension space to reflect the similarity of each entity In this paper, the optimization approach for the quantification analysis problem using neural networks is suggested, and the performance is analyzed The computation of average variation volume by mean field theory that is analytical approximated mobility of a molecule system and the annealed mean field neural network approach are applied in this paper for solving the quantification analysis problem. As a result, the suggested approach by a mean field annealing neural network can obtain more optimal solution than the eigen value analysis approach in processing costs.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.223-227
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• 1996

In this paper we propose an adaptive fast image restoration filter, which is suitable for reducing the blocking artifacts in the compressed image in real-time. The proposed restoration filter is based on the observation that quantization operation in a series of coding process is a nonlinear and many-to-one mapping operator. And then we propose an approximated version of constrained optimization technique as a restoration process for removing the nonlinear and space varying degradation operator. We also propose a novel block classification method for adaptively choosing the direction of a highpass filter, which serves as a constraint in the optimization process. The proposed classification method adopts the bias-corrected maximized likelihood, which is used to determine the number of regions in the image for the unsupervised segmentation. The proposed restoration filter can be realized either in the discrete Fourier transform domain or in the spatial domain in the form of a truncated finite impulse response (FIR) filter structure for real-time processing. In order to demonstrate the validity of the proposed restoration filter experimental results will be shown.

• Proceedings of the KSR Conference
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• 2004.06a
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• pp.589-594
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• 2004

In design of suspension system for KHST, it was applied the approximated optimization method using meta-models which called Response Surface Model and Neural Network Model for 29 design variables and 46 performance index. These models was coded using correlation between design variables and performance indices that is made by the 66 times iterative execution through the design of experimental table consisted orthogonal array L32 and D-Optimal design table. The results show that the optimization process is very efficient and simply applicable for complex mechanical system such as railway vehicle system. Also it was compared with the sensitivity of some design variables in order to know the characteristics of two models. This paper describes the general method for dynamic analysis and design process of railway vehicle system applied to KHST development, and proposed the efficient methods for vibration mode analysis process dealing with test data and the function based approximation method using meta-model applicable for a complex mechanical system. This method will be able to apply to the other railway vehicle system in oder to systematize and generalize the design process of railway vehicle dynamic system.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.3
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• pp.191-198
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• 2014

This paper proposes a simple linear function approximation method to solve an economic load dispatch problem with complex non-smooth generating cost function. This algorithm approximates a non-smooth power cost function to a linear approximate function and subsequently shuts down a generator with the highest operating cost and reduces the power of generator with more generating cost in order to balance the generating power and demands. When applied to the most prevalent benchmark economic load dispatch cases, the proposed algorithm is found to dramatically reduce the power cost than does heuristic algorithm. Moreover, it has successfully obtained results similar to those obtained through a quadratic approximate function method.

• Journal of Navigation and Port Research
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• v.29 no.5 s.101
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• pp.409-413
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• 2005

The existing control techniques for the operation of a container crane satisfy the terminal condition of controlled variables, but the outcome of input computation is inadequate for the operation of the crane due to heavy movement of inputs. In this study, a new control technique employing a nonlinear model of the crane is proposed to compute the inputs approximated with the 4th-order Chevyshev function. The control objective of sum of absolute deviations is minimized, and the optimization is conducted with the simplex algorithm. The inputs and outputs computed from the proposed technique were compared with the results of the previous study to show that they give more stable crane operation than the existing control technique.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.97-114
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• 2022

Interest is increasing in electrocardiogram (ECG) signal analysis for embedded devices, creating the need to develop an algorithm suitable for a low-power, low-memory embedded device. Linear approximation of the ECG signal facilitates the detection of fiducial points by expressing the signal as a small number of vertices. However, dynamic programming, a global optimization method used for linear approximation, has the disadvantage of high complexity using memoization. In this paper, the calculation area and memory usage are improved using a linear approximated template. The proposed algorithm reduces the calculation area required for dynamic programming through local optimization around the vertices of the template. In addition, it minimizes the storage space required by expressing the time information using the error from the vertices of the template, which is more compact than the time difference between vertices. When the length of the signal is L, the number of vertices is N, and the margin tolerance is M, the spatial complexity improves from O(NL) to O(NM). In our experiment, the linear approximation processing time was 12.45 times faster, from 18.18 ms to 1.46 ms on average, for each beat. The quality distribution of the percentage root mean square difference confirms that the proposed algorithm is a stable approximation.

• Journal of Advanced Navigation Technology
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• v.14 no.3
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• pp.446-451
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• 2010

This paper addressed an another scheme of distortion estimation method based on simplified inverse quantization in H.264/AVC. The distortion is calculated by the difference of coefficient between quantized transform coefficients and that of inverse. In general, these process included such transforms as discrete cosine transform(DCT), quantization, inverse quantization(IQ), and Inverse DCT(IDCT). In proposed approach, IQ as well as IDCT process are skipped because of replacing a couple of approximated formulas. Some simulation have been conducted and it showed that the PSNR was almost the same, and reduced the rate-distortion optimization(RDO) mode decision time of 8~15% in comparison with conventional method.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2600-2605
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• 2003

The PBL (Poly-butadiene Latex) production process is a typical batch process. Changes of the reactor characteristics due to the accumulated scaling with the increase of batch cycles require adaptive tuning of the PID controller being used. In this work we propose a tuning method for PID controllers based on the closed-loop identification and the genetic algorithm (GA) and apply it to control the PBL process. An approximated process transfer function for the PBL reactor is obtained from the closed-loop data using a suitable closed-loop identification method. Tuning is performed by GA optimization in which the objective function is given by ITAE for the setpoint change. The proposed tuning method showed good control performance in actual operations.

• International Journal of Aeronautical and Space Sciences
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• v.10 no.1
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• pp.46-58
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• 2009

This paper deals with design procedure of online guidance and control law for future missiles that requires agile maneuverability. For the purpose, the missile with high powered side thruster is proposed. The guidance and control law for such missiles is discussed from a point of view of optimal control theory in this paper. Minimum time problem is solved for the approximated system. It is derived that bang- bang control is optimal input from the necessary conditions of optimal solution. Feedback guidance without iterative calculation is useful for actual systems. In this paper. multiple design point method is applied to design feedback gains and feed forward inputs of the guidance and control law. The numerical results show that the proposed guidance and control law has a high -performance for wide-ranging boundary conditions.