• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.65-68
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• 2000

It is well-known that the decision rule in the mini-mum mean-squares-error decision feedback equalizer(MMSE-DFE) is biased, and therefore suboptimum with respect to error probability. We present a new family of algorithms that solve the bias problem in the adaptive DFE. A novel constraint, called the constant-norm con-straint, is introduced unifying the quadratic constraint and the monic one. A new cost function based on the constant-norm constraint and Lagrange multiplier is defined. Minimizing the cost function gives birth to a new family of unbiased adaptive DFE. The simula-tion results demonstrate that the proposed method in-deed produce unbiased solution in the presence of noise while keeping very simple both in computation and im-plementation.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.2
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• pp.111-119
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• 1995

In this paper, we propose an efficient SA(simulated annealing) algorithm for the synthesis of binary phase computer generated hologram. SA algorithm is a method to find the optimal solution through iterative technique. It is important that selecting cost function and parameters within this algorithm. The aplications of converentional SA algorithm to synthesize parameters within this algorithm. The applications of conventional SA algorithm to synthesize binary hologram have many problems because of inappropriate paramters and cost function. So, we propose a new cost function and a calculation technique of proper parameters required to achieve the optimal solution. Computer simulation results show that the proposed method is better than conventional method in terms of diffraction efficiency and reconstruction error. Also, we show the reconstructed images by the proposed method through optical esperiment.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.13 no.3
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• pp.200-208
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• 2001

In indoor temperature control of a heat pump, a reduction in energy consumption is very important. However, most control schemes for heat pumps have focused only on control performance such s settling time and steady-state error. In this paper, the model predictive control (MPC) which includes the energy-related variable in this cost function is proposed. By computing the control signal minimizing this cost function, the trade-off between energy reduction and temperature control performance can be obtained. Since the MPC required the process model, the dynamic mode of a heat pump is also obtained by the system identification technique. Performance of the proposed MPC considering energy efficiency is compared with the two other control schemes. It si shown that the proposed scheme can consume less energy thant hte others in achieving similar control performance.

• Journal of Power Electronics
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• v.19 no.1
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• pp.168-178
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• 2019

Discrete space vector modulation (DSVM) is an effective method to improve the steady-state performance of the finite control set predictive control for permanent magnet synchronous motor drive systems. However, it requires complex computations due to the presence of numerous virtual voltage vectors. This paper proposes an improved finite control set model-free predictive control using DSVM to reduce the computational burden. First, model-free deadbeat current control is used to generate the reference voltage vector. Then, based on the principle that the voltage vector closest to the reference voltage vector minimizes the cost function, the optimal voltage vector is obtained in an effective way which avoids evaluation of the cost function. Additionally, in order to implement double-objective control, a two-level decisional cost function is designed to sequentially reduce the stator currents tracking error and the inverter switching frequency. The effectiveness of the proposed control is validated based on experimental tests.

• Journal of IKEEE
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• v.19 no.3
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• pp.288-294
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• 2015

CRC function has been built into the high-speed semiconductor memory device in order to increase the reliability of data for high-speed operation. Also, DBI function is adopted to improve of data transmission speed. Conventional CRC(ATM-8 HEC code) method has a significant amounts of area-overhead(~XOR 700 gates), and processing time(6 stage XOR) is large. Therefore it leads to a considerable burden on the timing margin at the time of reading and writing of the low power memory devices for CRC calculations. In this paper, we propose a CRC method for low cost and high speed memory, which was improved 92% for area-overhead. For low-cost implementation of the CRC scheme by the DBI function it was supplemented by data bit error detection rate. And analyzing the error detection rate were compared with conventional CRC method.

• Journal of the Korean Society for Precision Engineering
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• v.11 no.4
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• pp.158-164
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• 1994

A volumetric error compensation method was stueide with measuring systematic error of a Coordinate Measuring Machine(CMM). The volumetric error equations were proposed for a Moving Bridge type CMM. Using the error equations, error vectors in the measuring volume were corrected by a software method. The CMM was controlled by the compensation program separately in the measuring and moving function of the CMM proving. The linear accuracy of the CMM was measured by the Laser Interferometer and compared with the data before the volumetric error compensation. This method was proved as low cost and effective to reduce the systematic error of the CMM, as no hardware modification is required.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.49 no.5
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• pp.264-268
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• 2000

In discuss how the existing study results that decide optimum release time are rational and reasonable, considering the cost and reliability simultaneously in this paper. As a study method this paper examines the proposed results and their methodologies centering around the existing related papers for the general cost-reliability optimal release policies, especially their limitation for the derived results.

• Journal of the Korean Society of Mechanical Technology
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• v.20 no.6
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• pp.809-817
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• 2018

The model predictive controller performance of the mobile robot is set to an arbitrary value because it is difficult to select an accurate value with respect to the controller parameter. The general model predictive control uses a quadratic cost function to minimize the difference between the reference tracking error and the predicted trajectory error of the actual robot. In this study, we construct a predictive controller by transforming it into a quadratic programming problem considering velocity and acceleration constraints. The control parameters of the predictive controller, which determines the control performance of the mobile robot, are used a simple weighting matrix Q, R without the reference model matrix $A_r$ by applying a quadratic cost function from which the reference tracking error vector is removed. Therefore, we designed the predictive controller 1 and 2 of the mobile robot considering the constraints, and optimized the controller parameters of the predictive controller using a genetic algorithm with excellent optimization capability.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.550-552
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• 2001

The vertically integrated power industry was divided into six generation companies and one market operator, where electricity trading was launched at power exchange. In this environment, the profits of each generation companies are guaranteed according to utilization of their own generation equipments. Especially, the electricity demand shows seasonal and weekly regular pattern, which the some capacity should be provided into ancillary service based on the past demand forecasting error and operating results of electricity market. Namely, if generation cost function is applied to SMP and BLMP as announced the previous day, the available generation capacity of the following day could be optimally distributed, and therefore contract capacity of ancillary service applied to CBP(Cost Based Pool) and TWBP(Two-Way Bidding Pool) is determined. Consequently, it is Possible to use the retained equipments optimally. This paper represents on efficient bidding strategies for generation equipments through the calculation of the contract and the application of each generator cost function based on the past demand forecasting error and market operating data.

• IE interfaces
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• v.17 no.spc
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• pp.122-130
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• 2004

Since the cost of software maintenance occupies about 50~75% in a general successful organization, the software maintenance plays an important role in software life cycle. In particular, if the managed system needs to be operated in a long term or the system is very large and complex, then the maintenance is especially more important. Software maintenance is defined as software modification activities after customer delivery, such as improvement of performance or functionality, error correction, adaptation to environmental changes, etc. In this paper, software cost estimation models are proposed, that is based on productivity of manpower in maintenance projects. In order to do this, the activities of maintenance are classified into function change, non-function change, user support and application operation. The proposed models are constructed and verified based on the real size and cost information of projects in the real world. The approach in this paper is to discriminate the heterogeneous activities in maintenance projects, and then to calculate the respective cost of each discriminated activity. By using the proposed models, the total cost of maintenance project is summed from the costs of four activities. In addition the number of conflicts between owner and order receiver about the amount of cost will be reduced and the reasonable cost estimation system will be established.