• Journal of the Korean Institute of Telematics and Electronics B
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• v.30B no.8
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• pp.54-63
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• 1993

This paper proposes a method for improving the performances of the neural network for optimization by an optimal estimation of initial states. The optimal initial state that leads to the global minimum is estimated by using the stochastic approximation. And then the update rule of Hopfield model, which is the high speed deterministic algorithm using the steepest descent rule, is applied to speed up the optimization. The proposed method has been applied to the tavelling salesman problems and an optimal task partition problems to evaluate the performances. The simulation results show that the convergence speed of the proposed method is higher than conventinal Hopfield model. Abe's method and Boltzmann machine with random initial neuron output setting, and the convergence rate to the global minimum is guaranteed with probability of 1. The proposed method gives better result as the problem size increases where it is more difficult for the randomized initial setting to give a good convergence.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.644-646
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• 1998

The main drawback of filtered-X LMS(FXLMS) algorithm for the ANC of broadband noises is its low convergence speed when the filtered reference signals are strongly correlated, producing a large eigenvalue spread in correlation matrix. This correlation can be caused either by autocorrelation of the signals of the reference sensors, or by coupling between the error path which introduces intercorrelation in the filtered reference signals. In this paper, we introduce a transform domain FXLMS(TD-FXLMS) algorithm that has a high convergence speed by orthogonal transform's decorrelation properties.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.8
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• pp.74-83
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• 1997

In this paper, we propose a new fractal image decoding algorithm with fast convergence speed by using the data dependence and the improved initial image estimation. Conventional method for fractal image decoding requires high-degrdd computational complexity in decoding process, because of iterated contractive transformations applied to whole range blocks. On proposed method, Range of reconstruction imagte is divided into referenced range and data dependence region. And computational complexity is reduced by application of iterated contractive transformations for the referenced range only. Data dependence region can be decoded by one transformations when the referenced range is converged. In addition, more exact initial image is estimated by using bound () function in case of all, and an initial image more nearer to a fixed point is estimated by using range block division estimation. Consequently, the convergence speed of reconstruction iamge is improved with 40% reduction of computational complexity.

• Journal of the Korean Society of Industry Convergence
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• v.25 no.6_2
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• pp.1071-1081
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• 2022

As the demand for high-rise buildings increases, the demand for high-speed elevators is also increasing. In order to make a high-speed elevator, a method is needed to reduce the weight of the elevator's components, which is a constraint on the increase in speed. As a measure to reduce the weight, it is possible to remove the traveling cable for power and signal supply. Since the weight of the traveling cable varies depending on the position of the carriage, it is difficult to compensate the weight using the counter weight. The power supply is a structure in which a brush-rail type power input terminal is installed in the elevator hoistway to receive power in a contact-type manner while the carriage is moving. If a small-capacity ESS is installed in a passenger car, power can be supplied uninterruptedly inside the passenger car. A small-capacity ESS charging system to be applied to such an elevator system is required to perform several functions. First, the passenger Car must be able to charge as much as possible even during high-speed operation. A control algorithm with high responsiveness is required because charging starts and ends repeatedly by the partially installed input power stage. In addition, if the input-side line impedance is large due to the structure of the system and the response characteristic is increased, the stability of the system may be lowered. Accordingly, in this paper, we propose a control algorithm that has a stable steady-state output while having a fast response in a transient state. To verify the proposed control algorithm, simulation was conducted using PSIM, and the performance of the controller was verified by manufacturing a prototype buck conveter charger.

• KDI Journal of Economic Policy
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• v.39 no.1
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• pp.19-40
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• 2017

This paper analyzes the interaction between monetary and macroprudential policies mainly in the context of the non-cooperation among policy authorities. Each policy authority's optimal response is to tighten its policy measures when other authorities' policy measures are loosened. This indicates that the two policies are substitutes for each other. This result still holds when an additional financial stability mandate is assigned to the central bank. The condition for the response functions to converge to a Nash equilibrium state is analyzed along with the speed of convergence, showing that they depend on the authorities' preferences and the number of mandates assigned to policy authorities. If the financial supervisory authority (FSA) assigns greater importance to the output gap or a stronger financial stability mandate is assigned to the central bank (CB), the probability of non-convergence increases and the speed of convergence declines even when the condition of convergence is satisfied. Meanwhile, if the CB considers output stability as an important task, the probability of convergence and the speed of converging to a state of equilibrium are high. Finally, when a single mandate or small number of mandates is/are assigned to each authority, stability is more quickly restored as compared to when many mandates are assigned.

• ETRI Journal
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• v.30 no.2
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• pp.183-193
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• 2008

In this paper, we propose quality of service mechanisms for flow-based routers which have to handle several million flows at wire speed in high-speed networks. Traffic management mechanisms are proposed for guaranteed traffic and non-guaranteed traffic separately, and then the effective harmonization of the two mechanisms is introduced for real networks in which both traffic types are mixed together. A simple non-work-conserving fair queuing algorithm is proposed for guaranteed traffic, and an adaptive flow-based random early drop algorithm is proposed for non-guaranteed traffic. Based on that basic architecture, we propose a dynamic traffic identification method to dynamically prioritize traffic according to the traffic characteristics of applications. In a high-speed router system, the dynamic traffic identification method could be a good alternative to deep packet inspection, which requires handling of the IP packet header and payload. Through numerical analysis, simulation, and a real system experiment, we demonstrate the performance of the proposed mechanisms.

• The KIPS Transactions:PartC
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• v.12C no.6 s.102
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• pp.839-846
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• 2005

Recently broadband convergence network technology is emerging as an integrated network of telecommunication, broadcasting and Internet. But there are various threats as side effects against the growth of information technology, and malicious codes such af Internet worms may bring about confusions to upset a national backbone network. In this paper, we survey the traditional spreading models and propose a new worm spreading model on Internet environment. We also analyze the spreading effects due to tile spread period and the response period of Internet worms. The proposed model leads to a better prediction of the scale and speed of worm spreading. It can be applied to high-speed network such as broadband convergence network.

• Design & Manufacturing
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• v.16 no.4
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• pp.40-45
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• 2022

The EV electric vehicle market is growing rapidly worldwide. An electric vehicle means a vehicle that uses energy charged through an electricity source as power. The precision of the press is important to mass-produce the drive motor, which is a key component of the electric vehicle. The size of the driving motor is increasing, and The size of the mold is also growing. In this study, the precision of large high-speed presses for mass production of driving motors was measured. A study was conducted on the measurement method of press and the analysis of measurement data. A drive motor is a component that transmits power by converting electrical energy into kinetic energy. EV driven motors have key material properties to improve efficiency. The material properties are the thickness of the material. As a method for improving performance, use a 0.2mm thin steel sheet. Mold is also becoming larger. As the mold grows, the size of the high-speed press for mass production of the driving motor is also increasing. Also, the precision of the press is the most important because it uses a thin iron plate material. So the importance of large press precision is being emphasized. In this study, the effect of large high-speed press structure on precision was verified

• Journal of Institute of Convergence Technology
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• v.4 no.2
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• pp.11-15
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• 2014

Magnet gear transfers a high speed torque of the driving side to a low speed following side. Of course, the torque is amplified as much as a ratio between pole number of magnet gears constituting both sides through ferromagnet modulator. However, the parameters of the overall magnetic system influence the transmitting torque strongly. They include a pole number of permanent magnet, magnet thickness, reducing ratio, harmonic modulator thickness, and open ratio etc. In this paper, the influences of the parameters are analyzed using finite element method tool. By comparison, a desirable design specification is proposed, including a recommended modulator pattern.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.4
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• pp.265-276
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• 2004

Genetic Algorithm(GA), that is shown stable performance to find an optimal solution, has been used as a method of solving large-scaled optimization problems with complex constraints in various applications. Since it takes so much time to execute a long computation process for iterative evolution and adaptation. In this paper, a hardware-based adaptive GA was proposed to reduce the serious computation time of the evolutionary process and to improve the accuracy of convergence to optimal solution. The proposed GA, based on steady-state model among continuos generation model, performs an adaptive mutation process with consideration of the evolution flow and the population diversity. The drawback of the GA, premature convergence, was solved by the proposed adaptation. The Performance improvement of convergence accuracy for some kinds of problem and condition reached to 5-100% with equivalent convergence speed to high-speed algorithm. The proposed adaptive GAP(Genetic Algorithm Processor) was implemented on FPGA device Xilinx XCV2000E of EHW board for face recognition.