• Journal of the Institute of Electronics Engineers of Korea CI
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• v.47 no.3
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• pp.59-66
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• 2010

This paper is proposed an adaptive fuzzy bilinear synchronization design for uncertain $L\ddot{u}$ chaos system. It is assumed that the $L\ddot{u}$ chaos system has unknown parameters. First, The $L\ddot{u}$ chaos system can be reconstructed via TS fuzzy bilinear modeling. We design an adaptive fuzzy bilinear synchronization control scheme based on TS fuzzy bilinear $L\ddot{u}$ chaos system with uncertain parameters. Lyapunov theory is employed to guarantee the stability of error dynamic system between TS fuzzy bilinear $L\ddot{u}$ chaos system and the proposed slave system and to derive the adaptive laws for estimating unknown parameters. Simulation results is given to demonstrate the validity of our proposed synchronization scheme.

• Journal of the Korean Data and Information Science Society
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• v.17 no.1
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• pp.95-113
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• 2006

The data resulting from a deterministic dynamic system may often appear to be random. However, it is important to distinguish a deterministic and a random processes for statistical analysis. In this paper, we propose a nonparametric test procedure to distinguish a noisy chaos from i.i.d. random process. The proposed procedure can be easily implemented by computer. We notice that the test is very effective to identify a low dimensional chaos process in some cases.

• Computational Structural Engineering
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• v.10 no.4
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• pp.239-249
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• 1997

The method to distinguish chaotic attractors in the perturbed response behaviors of a piecewise-linear system under combined regular and external randomness is provided and examined. In the noisy fields such as the ocean environment, excitation forces induced by wind, waves and currents contain a finite degree of randomness. Under external random perturbations, the system responses are disturbed, and consequently chaotic signatures in the response attractors are not distinguishable, but rather look just random-like. Mean Poincare map can be utilized to identify such chaotic responses veiled due to the random noise by averaging the noise effect out of the perturbed responses. In this study, the procedure to create mean Poincare map combined with the direct numerical simulations is provided and examined. It is found that mean Poincare maps can successfully distinguish chaotic attractors under stochastic excitations, and also can give the information of limit value of noise intensity with which the chaos signature in system responses vanishes.

• Journal of information and communication convergence engineering
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• v.1 no.1
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• pp.53-57
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• 2003

Chaos theory is a study researching the irregular, unpredictable behavior of deterministic and non-linear dynamical system. The interpretation using Chaos makes us evaluate characteristic existing in status space of system by tine series, so that the extraction of Chaos characteristic understanding and those characteristics enables us to do high precision interpretation. Therefore, This paper propose the new method which is adopted in extracting character features and recognizing characters using the Chaos Theory. Firstly, it gets features of mesh feature, projection feature and cross distance feature from input character images. And their feature is converted into time series data. Then using the modified Henon system suggested in this paper, it gets last features of character image after calculating Box-counting dimension, Natural Measure, information bit and information dimension which are meant fractal dimension. Finally, character recognition is performed by statistically finding out the each information bit showing the minimum difference against the normalized pattern database. An experimental result shows 99% character classification rates for 2,350 Korean characters (Hangul) using proposed method in this paper.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.297-299
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• 2003

This paper proposes a totally new method in the chaos characteristics analysis of power systems, the introduction of topological invariants. Using a return histogram the bifurcation graph was drawn, the periodic orbits and topological invariants the local crossing number, relative rotation rates, and linking number during the process of period-doubting bifurcation and chaos were extracted. This study also examined the effect on the topological invariants when the sensitive parameters were varied. In addition, the topological invariants of a three-dimensional embedding of the strange attractor was extracted and the result was compared with those obtained from differential equations. This could be a new way for a state detection and fault diagnosis in a dynamical system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.115-118
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• 2004

In this paper, a systematic design approach based on parallel distributed compensation techniques is proposed for anticontrol of chaos in a general continuous-time Takagi-Sugeno (TS) fuzzy system. The verification of chaos in the controlled continuous-time TS fuzzy system is done by the following procedure. First, we establish an asymptotically approximate relationship between a continuous-time TS fuzzy system with time-delay and a discrete-time TS fuzzy system. Then Marotto theorem is applied. The boundedness in the controlled continuous-time TS fuzzy system is also proven via its associated discrete-time TS fuzzy system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1009-1012
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• 1993

An association memory, solving an optimization problem, a Boltzmann machine scheme learning and a back propagation learning in our chaos neuron models are reviewed and some new results are presented. In each model its microscopicrule (a parameter of a chaos system in a neuron) is subject to its macroscopic state. This feedback and chaos dynamics are essential mechanisms of our model and their roles are briefly discussed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.853-856
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• 1993

In this paper, we describe a chaos simulator as a developing tool for applications of chaos engineering. This simulator is composed of three modules, such as generation module of chaotic signals by deterministic rules, determination module whether observed time series is chaos or not, and nonlinear system identification module by self generating Neuro Fuzzy Model.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.336-339
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• 2007

A chaos signal is used in all fields like engineering, a medical science and a biology very much, and study regarding the digital communication system that used a recent chaos signal is consisting actively. Applied a chaos signal in a digital communication system, and this paper designed six chaos signal generator to have been composed of by nonlinear equations as used System Generator, and implemented hardware to FPGA. Loaded bit stream to a FPGA board in order to verify this design to Hardware co-simulation from these results. Also, compared as investigated the maximum action frequency through timing analysis and resource of logic in order to evaluate performance of six chaos generator.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38A no.8
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• pp.638-643
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• 2013

Chaos communication system has a sensitive characteristic to initial conditions, because completely another signal is generated when initial condition of chaos equation is changed subtly. Also, chaos communication systems have the characteristics of non-periodic, non-predictability, the broadband signal, such as ease of implementation. Due to these characteristics, security of chaos communication system generally is evaluated better than other systems. However, BER(Bit Error Rate) performance is evaluated worse than other digital system, because existing chaos communication system's transmitter and receiver are strong influence by interference signal and noise. So, research to improve the BER performance of the chaotic communication system is performed continuously. In this paper, We will propose a new CDSK(Correlation Delay Shift Keying) receiver for BER performance improvement. After we compare to the performance of existing CDSK receiver and proposed CDSK receiver, BER performance of proposed CDSK receiver evaluate. Also, when using the new CDSK receiver, we evaluate the BER performance according to the spreading factors and find an optimum spreading factor. If chaos communication system use a new CDSK receiver, BER performance is improved than existing CDSK receiver. Also, if spreading factor's value is increased, BER performance is improved, because it is not nearly affected by interference signal and noise.