• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1093-1102
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• 2010

Even though the k-Nearest Neighbors Classification(KNNC) is one of the popular non-parametric classification methods, it does not consider the local features and class information for each observation. In order to overcome such limitations, several methods have been developed such as Adaptive Nearest Neighbors Classification(ANNC) and Modified k-Nearest Neighbors Classification(MKNNC). In this paper, we propose the Modified Adaptive Nearest Neighbors Classification(MANNC) that employs the advantages of both the ANNC and MKNNC. Through a real data analysis and a simulation study, we show that the proposed MANNC outperforms other methods in terms of classification accuracy.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.24 no.5
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• pp.574-580
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• 2013

Compared with the TWS(Track While Scan) tracking that uses scan-to-scan correlation at search illuminations for targets track, a phased array radar can use adaptive tracking which assigns additional track illuminations and the track formation range can be improved as a result. In this paper, an adaptive tracking, the search and track illuminations of a target are synchronized such that the extra illuminations are evenly distributed between the search illuminations, is proposed. Markov chain and track formation range for the proposed adaptive tracking are shown with them for the conventional TWS. The simulation result shows that the proposed adaptive tracking has improved track formation range by 27.6 % compared with the conventional TWS tracking under same track confirmation criterion.

• Journal of the Korean Statistical Society
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• v.13 no.1
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• pp.32-41
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• 1984

An adaptive distribution-free test is proposed for testing the equality of k independent distributions against unrestricted alternatives. In this paper, several rank-sum test statistics are considered as teh components of the adaptive one. The emprical powers of the adaptive testing procedure are compared to those of the classical F test and the component tests through a Monte Carlo study. The results show that the adaptive test has good power properties over a wide class of underlying distributions.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.454-456
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• 1998

Traditional adaptive control algorithms are not robust to dynamic uncertainties. The adaptive control algorithms developed previously to deal with dynamic uncertainties do not facilitate quantitative design. We proposed a new robust adaptive control algorithms consists of an $H^{\infty}$ suboptimal control law and a robust parameter estimator. Numerical examples showing the effectiveness of the $H^{\infty}$ adaptive scheme are provided.

• Journal of Welding and Joining
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• v.33 no.2
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• pp.47-55
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• 2015

With using adaptive control of the resistance spot welding machine, the advantage on electrode life time for galvanized steels has been addressed. This study was aimed to evaluate the electrode life time of galvanized steels with applying the constant current control and the adaptive control resistance spot welding process for a comparison purpose. The growth in diameter of electrode face was similar for both the constant current and the adaptive control up to 2000 welds. The button diameter was decreased with weld numbers, however, sudden increase in button diameter with use of the adaptive control after 1500 welds was observed. The peak load was continuously decreased with increasing number of welds for both the constant current and the adaptive control. The current compensation during a weld was observed with using the adaptive control after 1800 welds since the ${\beta}$-peak on dynamic resistance curve was detected at later weld time. The current compensation with adaptive control during resistance spot welding enhanced the nugget diameter at the faying interface of steel sheets and improved the penetration to thinner steel sheet.

• The Journal of the Acoustical Society of Korea
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• v.15 no.2E
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• pp.50-59
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• 1996

In this paper, an adaptive precompensator, which can reduce the distortion of a Wiener system effectively, is proposed. The previous techniques for adaptive precompensation, based on the Volterra series modeling to compensate the distortion of a nonlinear system, are not suitable for real-time implementation due to high computational burden and slow convergence burden and slow convergence rate. This paper presents an adaptive precompensation technique for the class of nonlinear subsystem, referred to as Wiener system. An adaptive algorithm for adjusting the parameters of a precompensator, structured by a hammerstein model, is derived using the stochastic gradient method. Also, an adaptive precompensatin technique which can effectively reduce nonlinear distortion in μ-law type of saturation characteristics is proposed. The validity of the proposed algorithm is confirmed through simulation by applying it to known Wiener systmes and a typical loudspeaker model.

• 제어로봇시스템학회:학술대회논문집
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• 1994.10a
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• pp.271-276
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• 1994

In this paper we deal with a design of CCV adaptive flight control system having adaptive observer under the mircroburst circumstances. First, based on the observerbility indices of the controlled system, which is a general multi-variable one, the adaptive observer is constructed, and the unknown interactor matrix can be estimated by using the identified parameters. Next, CCV adaptive flight control law is calculated based upon the estimated ones. Finally, the proposed CCV adaptive flight controller is applied to STOL flying boat and numerical simulations under the microburst circumstances can be show to justify the proposed scheme.

• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.1507-1508
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• 2008

In this paper, we propose a direct robust adaptive backstepping speed controller for induction motors system. A robust adaptive backstepping controller is designed using high order neural networks(HONN), which avoids the singularity problem in adaptive nonlinear control. The stability of the resulting adaptive system with proposed adaptive controller is guaranteed by suitable choosing the design parameter and initial conditions. HONN are used to approximate most of uncertainties which are derived from unknown motor parameters, load torque disturbances and unknown nonlinearities. The applicability of the proposed scheme is tested simulation.

• Journal of the Korean Statistical Society
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• v.30 no.3
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• pp.387-406
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• 2001

Adaptive estimators for a class of nonlinear time series models has been proposed by several authors. Koul and Schick(1997) proposed the adaptive estimators without sample splitting for location-type time series models. They also showed by simulation that the adaptive estimators without sample splitting have smaller mean squared errors than those of the adaptive estimators with sample splitting. the present paper generalized the result in a case of location-scale type nonlinear time series models by simulation.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.177-180
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• 1996

The purpose of this paper is to design a robust adaptive control algorithm for a class of systems having continuous relay nonlinearity. This continuous relay nonlinearity can be defined as an analytic nonlinear function having unknown parameters and bounded unmodeling part. By this mathematical modeling, the whole system can be considered as a nonlinear system having unknown parameters and bounded perturbation. The control algorithm of this paper, RALC, can be constructed by robust adaptive law, feedback linearization, and indirect robust adaptive control. By this RALC, we can obtain that the output of given system can follow that of a stable reference linear model made by designer and the boundedness of all signals in closed-loop system can be maintained. Therefore, we can confirm a robust adaptive control for a class of systems having continuous relay nonlinearity.