• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1995.10b
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• pp.33-39
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• 1995

One dimensional optimization problem is considered, we propose a method to find the global minimum of one-dimensional function with on gradient information but only the finite number of input-output samples. We construct a learning network which has a good learning capability and of which global maximum(or minimum) can be calculated with simple calculation. By teaching this network to approximate the given function with minimal samples, we can get the global minimum of the function. We verify this method using some typical esamples.

• 한국지구물리탐사학회:학술대회논문집
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• 2010.10a
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• pp.185-188
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• 2010

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.56-59
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• 1997

Vision system is mainly consist of three parts of perception, action. One of these parts, perception system detects visual target in surrounding environment. Block-based motion estimation with compensation is one of the popular approaches without accuracy. The hierarchical method the optical flow with gradient is used to improve optical flow time delay.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1-7
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• 1993

In this paper we propose the new adaptive control algorithm by using S-G algorithm based on the error equations derived by Slotine. We verify the validity of the proposed controller and convergence of three type parameter estimation law based on S-G algorithm from the computer simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1017-1021
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• 1991

This paper is to explore the potential use of the modeling capacity of neural networks for control applications. The tasks are carried out by two neural networks which act as a plant identifier and a system controller, respectively. Using information stored in the identification network control action has been developed. Without supervising control signals are generated by a gradient type iterative algorithm.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.1097-1112
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• 1989

An iterative learning control scheme is incorporated to the computed torque method as a means to enhance the accuracy and the flexibility. A learning rule is constructed by utilizing a gradient descent algorithm and data compressing techniques are illustrated. Computer simulation results show a good performance of the scheme under a relatively high speed and a heavy payload condition.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.2
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• pp.124-129
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• 2002

This paper demonstrates that the largest Lyapunov exponent λ of recurrent neural networks can be controlled efficiently by a stochastic gradient method. An essential core of the proposed method is a novel stochastic approximate formulation of the Lyapunov exponent λ as a function of the network parameters such as connection weights and thresholds of neural activation functions. By a gradient method, a direct calculation to minimize a square error (λ - λ$\^$obj/)$^2$, where λ$\^$obj/ is a desired exponent value, needs gradients collection through time which are given by a recursive calculation from past to present values. The collection is computationally expensive and causes unstable control of the exponent for networks with chaotic dynamics because of chaotic instability. The stochastic formulation derived in this paper gives us an approximation of the gradients collection in a fashion without the recursive calculation. This approximation can realize not only a faster calculation of the gradient, but also stable control for chaotic dynamics. Due to the non-recursive calculation. without respect to the time evolutions, the running times of this approximation grow only about as N$^2$ compared to as N$\^$5/T that is of the direct calculation method. It is also shown by simulation studies that the approximation is a robust formulation for the network size and that proposed method can control the chaos dynamics in recurrent neural networks efficiently.

• Journal of Korea Society of Industrial Information Systems
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• v.17 no.6
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• pp.51-58
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• 2012

Scirtothrips Dorsalis (Thysanoptera: Thripidae) recently has been recognized as a major source of the pest damage in the citrus fruit orchards. So its arrival has been predicted periodically but it is difficult to identify adults of the pest with the naked eyes because of their size smaller than the 0.8mm. In this paper, we propose a method to detect candidate areas for automatic identification of Scirtothrips Dorsalis on forecasting traps. The proposed method uses a histogram-based template matching where the composite image synthesized with the gray-scale image and the gradient image is used. In our experiments, images are acquired by the optical microscopy with 50 magnifications. To show the usefulness of the proposed method, it is compared with the method we previously suggested. Also, the performances when the proposed method is applied to noise-reduced images and gradient images are examined. The experimental results show that the proposed method is approximately 14.42% better than our previous method, 41.63% higher than the case that the noise-reduced image is used, and 21.17% higher than the case that the gradient image is used.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
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• v.8 no.3
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• pp.1-11
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• 2012

Mongolia has three(3) geothermal zones and eight(8) hydrogeothermal systems/regions that are, fold-fault platform/uplift zone, concave-largest subsidence zone, and mixed intermediate-transitional zone. Average temperature, heat flow, and geothermal gradient of hot springs in Arhangai located to fold-fault platform/uplift zone are $55.8^{\circ}C$, 60~110 mW/m2 and $35{\sim}50^{\circ}C/km$ respectively and those of Khentii situated in same zone are $80.5^{\circ}C$, 40~50 mW/m2, and $35{\sim}50^{\circ}C/km$ separately. Temperature of hydrothermal water at depth of 3,000 m is expected to be about $173{\sim}213^{\circ}C$ based on average geothermal gradient of $35{\sim}50^{\circ}C/km$. Among eight systems, Arhangai and Khentii located in A type hydrothermal system, Khovsgol in B type, Mongol Altai plateau in C type, and Over Arhangai in D type are the most feasible areas to develop geothermal power generation by Enhanced Geothermal System (EGS). Potential electric power generation by EGS is estimated about 2,760 kW at Tsenher, 1,752 kW at Tsagaan Sum, 2,928 kW at Khujir, 2,190 kW at Baga Shargaljuut, and 7,125 kW at Shargaljuut.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.5
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• pp.545-551
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• 2003

Henry System which is a traditional fingerprint classification model is difficult to apply to a modem Automatic Fingerprint Identification System (AFIS). To tackle this problem, this study is to apply algorithm for an An Ensemble Fingerprint Classroom System using changes of gradient of ridge in order to improve precise joining speed of a large volume of database. The existing classification system, Henry System, is useful in a captured fingerprint image of core point and delta point using paper and ink. However, the Henry System is unapplicable in modem Automatic Fingerprint Identification System (AFIS) because of problems such as size of input sensor and way of input. This study is to suggest an Ensemble Fingerprint Classroom System which can classify 5 basic patterns of Henry System in uncaptured delta image using changes of gradient of ridge. The proposed fingerprint classification technique will make an improvement of precise joining speed by reducing data volume.