• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.341-344
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• 2007

This paper proposes an alternative robust adaptive high-gain fuzzy observer design scheme and its application to synchronization of chaotic systems. The structure of the proposed observer is represented by Takagi-Sugeno fuzzy model and has the integrator of the estimation error. This improves the performance of high-gain observer and makes the proposed observer robust against noisy measurements, uncertainties and parameter perturbations as well. Using Lyapunov stability theory, an adaptive law is derived and the stability of the proposed observer is analyzed. Some simulation result is given to present the validity of theoretical derivations and the performance of the proposed observer.

• Structural Engineering and Mechanics
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• v.9 no.4
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• pp.397-416
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• 2000

The present study deals with the nonlinear dynamics and stability of autonomous dissipative either imperfect potential (limit point) systems or perfect (bifurcational) non-potential ones. Through a fully nonlinear dynamic analysis, performed on two simple 2-DOF models corresponding to the classes of systems mentioned above, and with the aid of basic definitions of the theory of nonlinear dynamical systems, new important phenomena are revealed. For the first class of systems a third possibility of postbuckling dynamic response is offered, associated with a point attractor on the prebuckling primary path, while for the second one the new findings are chaos-like (most likely chaotic) motions, consecutive regions of point and periodic attractors, series of global bifurcations and point attractor response of always existing complementary equilibrium configurations, regardless of the value of the nonconservativeness parameter.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.708-711
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• 1997

This paper proposes the hybrid algorithm for the optimization of the structure and parameters of the fuzzy neural networks by genetic algorithms (GA) to improve the behaviour and the design of fuzzy neural networks. Fuzzy neural networks have a distinguishing feature in that they can possess the advantage of both neural networks and fuzzy systems. In this way, we can bring the low-level learning and computational power of neural networks into fuzzy systems and also high-level, human like IF-THEN rule thinking and reasoning of fuzzy systems into neural networks. As a result, there are many research works concerning the optimization of the structure and parameters of fuzzy neural networks. In this paper, we propose the hybrid algorithm that can optimize both the structure and parameters of fuzzy neural networks. Numerical example is provided to show the advantages of the proposed method.

• Journal of Information Processing Systems
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• v.11 no.2
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• pp.310-324
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• 2015

The stream cipher Salsa20 and its reduced versions are among the fastest stream ciphers available today. However, Salsa20/7 is broken and Salsa20/12 is not as safe as before. Therefore, Salsa20 must completely perform all of the four rounds of encryption to achieve a good diffusion in order to resist the known attacks. In this paper, a new variant of Salsa20 that uses the chaos theory and that can achieve diffusion faster than the original Salsa20 is presented. The method has been tested and benchmarked with the original Salsa20 with a series of tests. Most of the tests show that the proposed chaotic Salsa of two rounds is faster than the original four rounds of Salsa20/4, but it offers the same diffusion level.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.975-979
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• 2001

In connection with the monitoring of the insulation degradation of large power apparatus in order to predict their expected service failures, a statistical treatment, such as phase resolved partial discharge analysis (PRPDA), has been established for the on-line monitoring system during the past decades. However, this method has shown some inconveniences to identify the nature of the PD source in power apparatus. In this regard, a novel approach based on the chaotic analysis (CAPD) is proposed describing the fundamental ideas, outcomes and different viewpoints from the conventional PRPDA. As a model for the possible defects causing sudden failures in service, three types of specimen are prepared. And partial discharge signals, originated from those samples, are measured and analyzed by means of CAPD. Throughout this work, it seems that the correlation between the consecutive PD pulses, depending on the nature of PD, could be clarified by CAPD. Thereffre, it could be considered that the nature of PD source can be identified more distinctively when the CAPD is combined with PRPDA.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1301-1304
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• 1998

Several neural networks have been successfully used to classify complex patterns such as handwritten numerals or words. This paper describes the discrimination of totally unconstrained handwritten numerals using the proposed chaotic neural network (CNN) to improve the recognition rate. The recognition system in the paper consists of the preprocessing stage to extract features using Kirsch mask and the classification stage to recognize numerals using the CNN. In order to evaluate the performance of the proposed network, we performed the recognition with unconstrained handwritten numeral database of Concordia university, Canada. Experimental results show that the CNN based recognizer performs higher recognition rate than other neural network-based methods reported using same database.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.125-128
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• 2005

This paper presents a simple methodolosy that makes a continuous-time nonlinear system chaotic using fuzzy control. The nonlinear system is represented by the T-S fuzzy model. Then, a fuzzy controller makes the T-S fuzzy model, which could be stable or unstable, bounded and chaotic. The verification of chaos in the closed-loop system is done by the following procedures. We establish an asymptotically approximate relationship between a continuous-time T-S fuzzy system with time-delay and a discrete-time T-S fuzzy system. Then, we verify the chaos in the closed-loop system by applying the Marotto theorem to its associated discrete-time T-S fuzzy system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2005.05a
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• pp.430-435
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• 2005

조화가진력이 작용하는 고정경계를 가진 완전원판의 비선형 진동에 대한 응답특성을 연구하였다. 원판의 비대칭모드의 고유진동수 근처에 가진주파수가 작용하는 주공진에서의 응답은 정상파(standing wave)뿐만 아니라 진행파(traveling wave)가 존재한다고 알려져 있다. 주공진 근처의 정상상태 응답곡선에서 최대한 5개의 안정한 응답이 존재하는 것으로 밝혀졌으며, 이들은 1개의 정상파와 4개의 진행파로 나타난다. 이 진행파중 2개는 Hope분기에 의해 안정성을 잃은 후 주기배가운동을 거쳐 혼돈운동에 이르게 된다. Lyaponov 지수를 사용하여 혼돈운동을 정량적으로 평가하였으며, 주평면의 개념을 이용하여 이 혼돈운동의 흡인영역이 Fractal임을 확인하였다.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1996.04a
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• pp.177-183
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• 1996

By utilizing the concept of normal modes, nonlinear dynamics is studied on pendulum dynamic absorber. When the spring mode loses the stability in undamped free system, a dynamic two-well potential is formed in Poincare map. A procedure is formulated to compute the forced responses associated with bifurcating mode and predict double saddle-loop phenomenon. It is found that quasiperiodic motion and stable periodic motion coexist in some parameter ranges, and only periodic motions or rotation of pendulum with chaotic fluctuation are observed in other ranges.

• Journal for History of Mathematics
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• v.17 no.2
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• pp.85-96
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• 2004

The Resealed range statistical analysis and Hurst exponent which are standard methods to test the chaotic model are used to examine sinusoid pattern. We notice that the Hurst exponent can be used as a measure to examine the time series data that show semi-cyclic trend with noise.