• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.466-469
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• 1996

In this paper, we present the global minimization condition by an informal analysis of the Langevine competitive learning neural network. From the viewpoint of the stochastic process, it is important that competitive learning guarantees an optimal solution for pattern recognition. By analysis of the Fokker-Plank equation for the proposed neural network, we show that if an energy function has a special pseudo-convexity, Langevine competitive learning can find the global minima. Experimental results for pattern recognition of handwritten numeral data indicate the superiority of the proposed algorithm.

• Journal of Power Electronics
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• 제2권3호
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• pp.220-229
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• 2002

In this paper, maximum efficiency operation of two types of permanent magnet synchronous motor drives, namely; surface type permanent magnet synchronous machine (SPMSM) and interior type permanent magnet synchronous motor(IPMSM), are investigated. The efficiency of both drives is maximized by minimizing copper and iron losses. Loss minimization is implemented using flux weakening. A neural network controller (NNC) is designed for each drive, to achieve loss minimization at difffrent speeds and load torque values. Data for training the NNC are obtained through off-line simulations of SPMSM and IPMSM at difffrent operating conditions. Accuracy and fast response of each NNC is proved by applying sudden changes in speed and load and tracking the UC output. The drives'efHciency obtained by flux weakening is compared with the efficiency obtained when setting the d-axis current component to zero, while varying the angle of advance "$\vartheta$" of the PWM inverter supplying the PMSM drive. Equal efficiencies are obtained at diffErent values of $\vartheta$, derived to be function of speed and load torque. A NN is also designed, and trained to vary $\vartheta$ following the derived control law. The accuracy and fast response of the NN controller is also proved.so proved.

• 한국방송∙미디어공학회:학술대회논문집
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• 한국방송공학회 2010년도 하계학술대회
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• pp.138-141
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• 2010

In this paper, we propose a semi-automatic method for semantic video object extraction which extracts meaningful objects from an input sequence with one correctly segmented training image. Given one correctly segmented image acquired by the user's interaction in the first frame, the proposed method automatically segments and tracks the objects in the following frames. We formulate the semantic object extraction procedure as an energy minimization problem at the fragment level instead of pixel level. The proposed energy function consists of two terms: data term and smoothness term. The data term is computed by considering patch similarity, color, and motion information. Then, the smoothness term is introduced to enforce the spatial continuity. Finally, iterated conditional modes (ICM) optimization is used to minimize energy function in a globally optimal manner. The proposed semantic video object extraction method provides faithful results for various types of image sequences.

• Journal of Computing Science and Engineering
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• 제4권3호
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• pp.189-206
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• 2010

It is generally accepted that dynamic voltage scaling (DVS) is one of the most effective techniques of energy minimization for real-time applications in embedded system design. The effectiveness comes from the fact that the amount of energy consumption is quadractically proportional to the voltage applied to the processor. The penalty is the execution delay, which is linearly and inversely proportional to the voltage. According to the granularity of tasks to which voltage scaling is applied, the DVS problem is divided into two subproblems: inter-task DVS problem, in which the determination of the voltage is carried out on a task-by-task basis and the voltage assigned to the task is unchanged during the whole execution of the task, and intra-task DVS problem, in which the operating voltage of a task is dynamically adjusted according to the execution behavior to reflect the changes of the required number of cycles to finish the task before the deadline. Frequent voltage transitions may cause an adverse effect on energy minimization due to the increase of the overhead of transition time and energy. In addition, DVS needs to be carefully applied so that the dynamically varying chip temperature should not exceed a certain threshold because a drastic increase of chip temperature is highly likely to cause system function failure. This paper reviews representative works on the theoretical solutions to DVS problems regarding inter-task DVS, intra-task DVS, voltage transition, and thermal-aware DVS.

• Journal of Electrical Engineering and Technology
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• 제9권6호
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• pp.1843-1850
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• 2014

In this paper, we investigate a group building based power consumption scheduling to minimize the electricity cost. We consider the demand shift to reduce the peak load and suggest the compensation function reflecting the relationship between the change of the building demand and the occupants' comfort. Using that, the electricity cost minimization problem satisfied the convexity is formulated, and the optimal power consumption scheduling algorithm is proposed based on the iterative method. Extensive simulations show that the proposed algorithm achieves the group management gain compared to the individual building operation by increasing the degree of freedom for the operation.

• 전자공학회논문지S
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• 제34S권1호
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• pp.72-79
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• 1997

Most open magnetic resonance imaging systems have used the planar gradient coils whose inductances were minimized through the magnetic energy minimization procedure in the spatial frequency domain. Though the planar gradient coils have smaller inductance than conventional gradient coils, the planar gradient coils often suffer from their poor magnetic field linearity. Scaling the spatial frequencies of the current density function designed by the magnetic energy minimization, magnetic field linearity of the planar gradient coils can be greatly improved with small sacrifice of gradient coil inductance. We have found that the figure of merit of the planar gradient coils, defined by the gradient strength divided by the linearity error and the inductance, can be improved by proposed technique.

• Journal of Power Electronics
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• 제8권4호
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• pp.345-353
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• 2008

In this paper, a novel loss minimization of an induction generator in wind energy generation systems is presented. The proposed algorithm is based on the flux level reduction, for which the generator d-axis current reference is estimated using support vector regression (SVR). Wind speed is employed as an input of the SVR and the samples of the generator d-axis current reference are used as output to train the SVR algorithm off-line. Data samples for wind speed and d-axis current are collected for the training process, which plots a relation of input and output. The predicted off-line function and the instantaneous wind speed are then used to determine the d-axis current reference. It is shown that the effect of loss minimization is more significant at low wind speed and the loss reduction is about to 40% at 4[m/s] wind speed. The validity of the proposed scheme has been verified by experimental results.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2002년도 봄 학술발표회 논문집
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• pp.361-368
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• 2002

A new remeshing algorithm based on the energy minimization is proposed for the finite element method. This utilizes the variation of mapping function between the master and global elements. The resultant equations are only the other form of the governing equations. However the equations have an important information about the relations between the elements. By assuming the solutions of the governing equations, these relations are used very usefully for the mesh optimization. The explicit formulations are presented for the relations of 1-dimensional equations and some examples are solved for comparison with the other methods. In addition, 2-dimensional expansion is presented for the general use.

• 대한의용생체공학회:학술대회논문집
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• 대한의용생체공학회 1996년도 추계학술대회
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• pp.165-168
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• 1996

Though the planar gradient coils, designed by the magnetic energy minimization procedure, have smaller inductance than conventional gradient coils, the planar gradient oils often suffer from their poor magnetic field linearity. Scaling the spatial frequencies of the current density function designed by the magnetic energy minimization procedure, magnetic field linearity of the planar gradient coils can be featly improved with small sacrifice of gradient coil inductance.

• 한국멀티미디어학회논문지
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• 제22권4호
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• pp.491-501
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• 2019

Variational methods, which cast deformation as an energy-minimization problem, are known to provide a good trade-off between practicality and speed. However, the time required to deform a fully detailed shape means that these methods are largely unsuitable for real-time applications. We simplify a 2D shape into a curve skeleton, which can be deformed much more rapidly than the original shape. The curve skeleton also provides a simplified control for the user, utilizing a small number of control handles. Our system deforms the curve skeleton using an energy-minimization method and then applies the resulting deformation to the original shape using linear blend skinning. This approach effectively reduces the size of the variational optimization problem while producing deformations of a similar quality to those obtained from full-scale nonlinear variational methods.