• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.1021-1024
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• 2000

In this paper, a neuro-fuzzy system for quantitative characterization of chaotic signals is proposed. The proposed system is differ from the previous methods in that the nonlinear functions of the nonlinear dynamical systems are calculated as the invariant factor. In the proposed neuro-fuzzy system, the nonlinear functions are determined by supervised learning. From the reconstructed nonlinear functions, the proposed system can generate extrapolated chaotic signals. This feature will help the study of nonlinear dynamical systems which require large number of chaotic data. To confirm the validity of the proposed system, nonlinear functions are reconstructed from 1-dimensional and 2-dimensional chaotic signals.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.15 no.3E
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• pp.45-59
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• 1996

Generalized iterative methods for reducing noise in contaminated chaotic signals are proposed. These methods minimize a cost function composed of two parts : one containing information that represents how close enhanced signals are to the observed signal and another composed of constraints that fit the dynamics of the system. The convergence conditions and the error systems of the proposed are investigated. As one aspect of noise reduction, the suppression or cancellation of a chaotic interference signal is discussed.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.869-872
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• 1993

The chaotic fuzzy logic systems behave in a more complex way than crisp chaotic systems, and they can show some advantages in complex applications. Such an application is introduced in this paper, namely in scrambling and ciphering the signals.

• Journal of information and communication convergence engineering
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• v.8 no.5
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• pp.560-565
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• 2010

In this study, the existence of chaotic characteristics in snoring signals obtained in the form of time series data was checked through quantitative and qualitative analysis methods, and a snoring signal detection system was designed applied with detection algorithms considering diverse parameters of occurring signals in order to enhance the accuracy and reliability of detections and the performance of the system was checked. The system was tested with certain snoring patients and thereby the results as follows could be obtained.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2136-2139
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• 2008

Chaotic oscillators can generate wide-band signals and the spectrum characteristics of the wide-band signals are not changed by switching on and off the output power of the oscillators. When communication systems use a chaotic oscillator, the communication system need not a local oscillator and a mixer used in conventional transceivers. Therefore the configuration of a communication system using a chaotic oscillator is simple and have the characteristics of low-power consumption. In this paper we design and implement a chaotic oscillator. And the test results of the implemented chaotic oscillator for UWB systems are presented. The implemented chaotic oscillator has -8.11dBm of the output power with 500MHz channel bandwidth at 3.4GHz of the center frequency and has about 410MHz of -10dB bandwidth.

• Convergence Security Journal
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• v.8 no.3
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• pp.57-64
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• 2008

The Security of digital images has become increasingly more important in highly computerized and interconnected world. Therefore, The chaos-based encryption algorithms have suggested some new and efficient ways to develop secure image encryption method. This paper is described for the point at issue in all chaos-based encryption method for distribution of a chaotic signals. It has a method for generation of uniformly distributed chaotic signals that we designed secure algorithm of multi-parameter chaotic systems. So we are present validity of the theoretical models for results of image encryption and decryption for proposed method.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.9 no.2
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• pp.45-51
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• 2000

This study proposes that analysis and evaluation method of time series ultrasonic signal using the chaotic feature extrac-tion for degradation extent. Features extracted from time series data using the chaotic time series signal analyze quantitatively material degradation extent. For this purpose analysis objective in this study if fractal dimension lyapunov exponent and strange attractor on hyperspace. The lyapunov exponent is a measure of the rate at which nearby trajectories in phase space diverge. Chaotic trajectories have at least one positive lyapunov exponent. The fractal dimension appears as a metric space such as the phase space trajectory of a dynamical syste, In experiment fractal(correlation) dimensions and lyapunov experiments showed values of mean 3.837-4.211 and 0.054-0.078 in case of degradation material The proposed chaotic feature extraction in this study can enhances ultrasonic pattern recognition results from degrada-tion signals.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.407-410
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• 1996

In this Paper, we propose the feedback method having neural network to control the chaotic signals to periodic signals. This controller has very simple structure, it is immune to small parameter variations, the precise access to system parameters is not required and it is possible to follow ones of its inherent periodic orbits or the desired orbits without error, The controller consist of linear feedback gain and neural network. The learning of neural network is achieved by error-backpropagation algorithm. To prove and analyze the proposed method, we construct a software tool using c-language.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.294-297
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• 1996

This paper proposes the method to recognize of time series data based on the chaotic feature extraction. Features extract from time series data using the chaotic time series data analysis and the pattern recognition process is using a neural network classifier. In experiment, EEG(electroencephalograph) signals are extracted features by correlation dimension and Lyapunov experiments, and these features are classified by multilayer perceptron neural networks. Proposed chaotic feature extraction enhances recognition results from chaotic time series data.