• Title/Summary/Keyword: Chaotic Response

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A Study on the Convergence Characteristics Analysis of Chaotic Dynamic Neuron (동적 카오틱 뉴런의 수렴 특성에 관한 연구)

  • Won-Woo Park
    • Journal of the Institute of Convergence Signal Processing
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    • v.5 no.1
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    • pp.32-39
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    • 2004
  • Biological neurons generally have chaotic characteristics for permanent or transient period. The effects of chaotic response of biological neuron have not yet been verified by using analytical methods. Even though the transient chaos of neuron could be beneficial to overcoming the local minimum problem, the permanent chaotic response gives adverse effect on optimization problems in general. To solve optimization problems, which are needed in almost all neural network applications such as pattern recognition, identification or prediction, and control, the neuron should have one stable fixed point. In this paper, the dynamic characteristics of the chaotic dynamic neuron and the condition that produces the chaotic response are analyzed, and the convergence conditions are presented.

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Chaotic Response of a Nonlinear Vehicle Model and Elimination of the Chaos

  • Lai, Edmund;Park, Chan-Gook
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.106.6-106
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    • 2001
  • In this paper, a four-degree-of-freedom non-linear model is developed to study the dynamic response of vehicle that is caused by the disturbance from the road. The chaotic vibration of the model is investigated with numerical simulation. The model displays complicated dynamic responses including harmonic motions and chaos. It is found that changing of the damping coefficients of the system can eliminate the chaotic response.

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A Study of Chaotic Responses of an Elastic-Plastic Beam Model to Periodic Impulsive Force (주기적인 충격력을 받는 탄소성 보의 케이오틱거동 연구)

  • 이재영
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.19 no.5
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    • pp.1158-1167
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    • 1995
  • In this study, the dynamic instabilities of a beam, subjected to periodic short impulsive loading, are investigated using simple 2-DoF beam model. The behaviors of beam model whose axial motions are constrained are studied for the case of elastic and elastic-plastic behavior. In the case of elastic behavior, the chaotic responses due to the periodic pulse are identified, and the characteristics of the behavior are analysed by investigating the fractal attractors in the Poincare map. The short-term and long-term responses of the beam are unpredictable because of the extreme sensitivities to parameters, a hallmark of chaotic response. In the case of elastic-plastic behavior, the responses are governed by the plastic strains which occur continuously and irregularly as time increases. Thus the characteristics of the response behavior change continuously due to the plastic strain increments, and are unpredictable as well as the elastic case.

The Single Step Prediction of Multi-Input Multi-Output System using Chaotic Neural Networks (카오틱 신경망을 이용한 다입력 다출력 시스템의 단일 예측)

  • 장창화;김상희
    • Proceedings of the IEEK Conference
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    • 1999.06a
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    • pp.1041-1044
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    • 1999
  • In This paper, we investigated the single step prediction for output responses of chaotic system with multi Input multi output using chaotic neural networks. Since the systems with chaotic characteristics are coupled between internal parameters, the chaotic neural networks is very suitable for output response prediction of chaotic system. To evaluate the performance of the proposed neural network predictor, we adopt for Lorenz attractor with chaotic responses and compare the results with recurrent neural networks. The results demonstrated superior performance on convergence and computation time than the predictor using recurrent neural networks. And we could also see good predictive capability of chaotic neural network predictor.

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A study on the Convergence Condition of Chaotic Dynamic Neural Networks

  • Kim, Sang-Hee;Wang, Hua O.
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.7 no.4
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    • pp.242-248
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    • 2007
  • This paper analyzes on the chaos characteristics of the chaotic neural networks and presents the convergence condition. Although the transient chaos of neural network sould be beneficial to overcome the local minimum problem and speed up the learning, the permanent chaotic response gives adverse effect on optimization problems and makes neural network unstable in general. This paper investigates the dynamic characteristics of the chaotic neural networks with the chaotic dynamic neuron, and presents the convergence condition for stabilizing the chaotic neural networks.

Chaotic Synchronization of Using HVPM Model (HVPM 모델을 이용한 카오스 동기화)

  • 여지환;이익수
    • Journal of Korea Society of Industrial Information Systems
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    • v.6 no.4
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    • pp.75-80
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    • 2001
  • In this paper, we propose a new chaotic synchronization algorithm of using HVPM(Hyperchaotic Volume Preserving Maps) model. The proposed chaotic equation, that is, HVPM model which consists of three dimensional discrete-time simultaneous difference equations and shows uniquely random chaotic attractor using nonlinear maps and modulus function. Pecora and Carrol have recently shown that it is possible to synchronize a chaotic system by sending a signal from the drive chaotic system to the response subsystem. We proposed coupled synchronization algorithm in order to accomplish discrete time hyperchaotic HVPM signals. In the numerical results, two hyperchaotic signals are coupled and driven for accomplishing to the chaotic synchronization systems. And it is demonstrated that HVPM signals have shown the chaotic behavior and chaotic coupled synchronization.

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Analyses of Encryption Method for Chaos Communication Using Optical Injection Locked Semiconductor Lasers (반도체 레이저의 광 주입을 이용한 혼동 통신망의 암호화 기법 분석)

  • Kim Jung-Tae
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.4
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    • pp.811-815
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    • 2005
  • We theoretically studied synchronization of chaotic oscillation in semiconductor lasers with chaotic light injection feed-back induced chaotic light generated from a master semiconductor laser was injected into a solitary slave semiconductor laser. The slave laser subsequently exhibited synchronized chaotic output for a wide parameter range with strong injection and frequency detuning within the injection locking scheme. We also analytically examined chaos synchronization based on a linear stability analysis from the view point of synchronization based on a linear stability analysis from the view point of modulation response of injection locked semiconductor lasers to chaotic light signal.

T-S Fuzzy Model-Based Adaptive Synchronization of Chaotic System with Unknown Parameters (T-S 퍼지 모델을 이용한 불확실한 카오스 시스템의 적응동기화)

  • Kim, Jae-Hun;Park, Chang-Woo;Kim, Eun-Tai;Park, Mignon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.2
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    • pp.270-275
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    • 2005
  • This paper presents a fuzzy model-based adaptive approach for synchronization of chaotic systems which consist of the drive and response systems. Takagi-Sugeno (T-S) fuzzy model is employed to represent the chaotic drive and response systems. Since the parameters of the drive system are assumed unknown, we design the response system that estimates the parameters of the drive system by adaptive strategy. The adaptive law is derived to estimate the unknown parameters and its stability is guaranteed by Lyapunov stability theory. In addition, the controller in the response system contains two parts: one part that can stabilize the synchronization error dynamics and the other part that estimates the unknown parameters. Numerical examples, including Doffing oscillator and Lorenz attractor, are given to demonstrate the validity of the proposed adaptive synchronization approach.

On the Chaotic Vibrations of Thin Beams by a Bifurcation Mode (분기 모우드를 활용한 얇은 빔의 혼돈 역학에 관한 연구)

  • 이영섭;주재만;박철희
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 1995.04a
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    • pp.121-128
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    • 1995
  • The results are summarized as what follows: 1) The modeling of thin beams, which is a continuous system, into a two DOF system yields satisfactory results for the chaotic vibrations. 2) The concept of "natural forcing function" derived from the eigenfunction of the bifurcation mode is very useful for the natural responses of the system. 3) Among the perturbation techniques, HBM is a good estimate for the response when the geometry of motion is known. 4) It is known that there exist periodic solutions of coupled mode response for somewhat large damping and forcing amplitude, as well as weak damping and forcing. 5) The route-to-chaos related with lateral instability in thin beams is composed of period-doubling and quasiperiodic process and finally follows discontinuous period-doubling process. 6) The chaotic vibrations are verified by using Poincare maps, FFT's, time responses, trajectories in the configuration space, and the very powerful technique Lyapunov characteristics exponents.exponents.

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Chaotic Response of a Spherical Shell to Impulsive Loading (충격력을 받는 구형 쉘의 혼돈거동 해석)

  • 이재영;강영철
    • Computational Structural Engineering
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    • v.10 no.3
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    • pp.167-174
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    • 1997
  • Engineers must be aware of possible sources of chaotic behavior. They may render conventional design predictions untrustworthy and potentially unsafe because of the sensitivity to initial conditions. Dynamic responses of a spherical shell subjected to impulsive loading which act on the center are analyzed using the finite element method. The chaotic responses are identified by the standard methods, such as displacement-time histories, Poincare maps, and phase diagrams. The responses are chaotic, but, not so sensitive to the initial conditions, and the characteristics of responses are not changed with time, in contrast to the case of the responses of beam. The Poincare points scattered in the limited area represent that the responses are chaotic, but do not show the geometric structures. The snap-through phenomena of the shell to the side of the direction of the load or of the opposite direction, is analysed by using the energy diagram.

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