• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.962-964
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• 1995

In this paper, an integrated chaos analysis system for EEG (ICASE) is designed for the analysis of brain functions based on the chaos theory. Nonlinear dynamic characteristics of EEG such as 3-D attractor, Poincare section, correlation dimension, Lyapunov exponents and power spectrum are extracted by this system. The results show that chaotic attractors which indicate the presence of deterministic, dynamics of complex nature could be identified from a routine EEG recording for normal and pathological activity. This proves that the chaotic analysis of EEG may be an appropriate tool in the classification of brain activity and thus a possible diagnostic tool.

• Journal of applied mathematics & informatics
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• v.41 no.1
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• pp.107-121
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• 2023

An epidemic infectious disease model consists of six compartments viz. Susceptible, Exposed, Infected, Quarantine, Recovered, and Virus with nonlinear saturation incidence rate is proposed to know the viral disease dynamics. There exist two biological equilibrium points for the model system. The system's local and global stability is done through Lyapunov's direct method about equilibrium points. The sensitivity analysis has been performed for the basic reproduction number and equilibrium points through the normalized forward sensitivity index. Sensitivity analysis shows that virus growth and quarantine rates are more sensitive parameters. In support of mathematical conclusions, numerical experimentation has been shown.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1997.04a
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• pp.62-67
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• 1997

This paper reprdsents a new scheme of neural network control system analysis the robustues of robot manipulator using digital signal processors. Digtal signal processors, DSPs, are micro-processors that are particularly developed for fast numerical computations involving sums and products of variables. Digital version of most advanced control algorithms can be defined as sums and products of measured variables, thus it can be programmed and executed through DSPs. In additions, DSPs are a s fast in computation as most 32-bit micro-processors and yet at a fraction of their prices. These features make DSPs a viable computational tool in digital implementation of sophisticated controllers. Durng past decade it was proposed the well-established theorys for the adaptive control of linear systems, but there exists relatively little general theory for the adaptive control of nonlinear systems. The proposed neuro network control algorithm is one of learning a model based error back-propagation scheme using Lyapunov stability analysis method.

• Journal of the Korean Mathematical Society
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• v.49 no.3
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• pp.641-658
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• 2012

The goal of this paper is to develop a nonlinear observer-based control strategy for a multi-variables continuous stirred tank reactor (CSTR). A new robust nonlinear observer is constructed to estimate the whole process state variables. The observer is coupled with a nonlinear controller, designed based on the input-output linearization for controlling the concentration and reactor temperature. The closed loop system is shown to be globally asymptotically stable based on Lyapunov arguments. Finally, computer simulations are developed for showing the performance of the proposed controller.

• Journal of the Korean Society for Precision Engineering
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• v.14 no.11
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• pp.93-101
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• 1997

Ever since the nonlinearity of machine tool dynamics was established, researchers attempted to make use of this fact to devise better monitoring, diagnostics and control system, which were hitherto based on linear models. Theory of chaos which explains many nonlinear phenomena comes handy for furthering the analysis using nonlinear model. In this study, measuring system will be constructed using multi-sensor (Tool Dynamometer, Acoustic Emission) in end milling process. Then, it will be verified that cutting force is low-dimensional chaos by calculating Lyapunov exponents. Fractal dimension, embedding dimension. And it will be investigated that the relation between characteristic parameter calculated from sensor signal and tool wear.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.801-803
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• 1995

This paper presents the linearized fuzzy modeling technique of nonlinear dynamical system and the stability analysis of fuzzy control system. Firstly, the nonlinear system is partitionized by multiple linear fuzzy subcontrol systems based on fuzzy linguistic variables and fuzzy rules. Secondly, the disturbance adaptation controllers which guarrantee the global asymptotic stability of each fuzzy subsystem by an optimal feedback control law are designed and the stability analysis procedures of the total fuzzy control system using Lyapunov functions and eigenvalues are discussed in detail through a given illustrative example.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.43 no.5
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• pp.693-702
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• 1994

This paper deals with direct voltage stability analysis using a power system energy function. The structure preserved energy function is proposed as an energy function for voltage stability analysis. With the use of the proposed energy function voltage collapse conditions are derived, which yields the exactly same results with the Jacobian matrix approach. The voltage collapse phenomenon is analyzed by several methods, which shows that all of the methods produce the same voltage condition. This study also investigates the voltage collapse dynamics by using the proposed energy function. As a result, it has been found that the voltage collapse can be classified into two categories: static and dynamic instablilties which have quite different behaviors. In addition a new method is presented to calculate the power capacity limit of transmission lines with respect to voltage stability. The proposed method is tested for a 2-bus sample system, which shows the characteristics of voltage collapse phenomenon via the energy function.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.129-142
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• 1996

The early diagnosis has an very important role in curing dementia. But there was not the effective method to diagnose it until now. In this paper we analyzed the EEG of Alzheimer's disease patients and normal groups by nonlinear methods. In the analysis we calculated the correlation dimensions $D_2$ and the largest Lyapunov exponent $L_1$. We found that patients with Alzheimer's disease have significantly lower $D_2$ and TEX>$L_1$ than normal groups. It means that brains injured by Alzheimer's disease have electrophysiological inactive elements and have decreased chaotic behaviour. We propose the nonlinear analysis of the EEG as a useful tool for the early diagnosis of Alzheimer's disease.

• Nonlinear Functional Analysis and Applications
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• v.26 no.3
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• pp.629-648
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• 2021

In this paper, we study a within-host mathematical model of HCV infection and carry out mathematical analysis of the global dynamics and bifurcations of the model in different parameter regimes. We explore the effect of reverse transcriptase inhibitors (RTI) on spontaneous HCV clearance. The model can produce all clinically observed patient profiles for realistic parameter values; it can also be used to estimate the efficacy and/or duration of treatment that will ensure permanent cure for a particular patient. From the results of the model, we infer possible measures that could be implemented in order to reduce the number of infected individuals.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.05a
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• pp.803-806
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• 2012

On this paper, various analysis methods has been applied to analyze and forecast the maximum electrical power needs, which is regarded as a nonlinear dynamic system. To understand the characteristic of complicated system, we used TISEAN package and evaluate the chaotic characteristic of time series obtained from electrical power demand using it. TISEAN package offers various algorithms and codes to analyze time series of nonlinear system effectively.