• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.9
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• pp.1528-1543
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• 2011

With increasing the using of wireless technologies in essential fields such as the medical application, this paper proposes different scenarios for the transmission of images over wireless networks. The paper uses the IEEE ZigBee 802.15.4 for applying the proposed schemes. It is a Wireless Personal Area Network (WPAN). This paper presents a novel chaotic interleaving scheme against error bursts. Also, the paper studies the proposed interleaver with the convolutional code with different constraint lengths (K). A comparison study between the standard scheme and proposed schemes for image transmission over a correlated fading channel is presented. The simulation results show the superiority of the proposed chaotic interleaving scheme over the traditional schemes. Also, the chaotic interleaver packet-by-packet basis gives a high quality image with (K=3) and reduces the need for the complex encoder with K=7.

• Korean Journal of Biological Psychiatry
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• v.2 no.2
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• pp.257-265
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• 1995

The object of this study is to apply a chaotic signal analysis method to the EEG research, especially in the aspect of neuropsychiatry, and to get some inspection of the chaotic phenomena according to the brain sites and subjects. We have acquired 21 channel EEG data and one EOG according to the international 10-20 system and calculated the correlation dimension. The subject groups are schizophrenics, bipolar disorder, major depression and normal control. They were all awoke and eye-closed. We have found no distinctive features from our experiments except temporal regions have slightly higher correlation dimension. There is also no specific distinctions between groups. We conjecture that these results are mainly because the subjects were not well controlled. EEG dimension may change in accordance with to the age, sex, medication and the time data were selected to calculate. We have also considered some conditions for a better and more objective research of chaotic analysis to EEG research. Better conditioning and standardizing the calculation of correlation dimension is necessary for the application of the chaotic analysis to neuropsychiatry.

• Journal of Computing Science and Engineering
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• v.8 no.4
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• pp.187-198
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• 2014

In this paper an efficient image encryption scheme based on cyclic rotations and multiple blockwise diffusions with two chaotic maps is proposed. A Sin map is used to generate round keys for the encryption/decryption process. A Pomeau-Manneville map is used to generate chaotic values for permutation, pixel value rotation and diffusion operations. The encryption scheme is composed of three stages: permutation, pixel value rotation and diffusion. The permutation stage performs four operations on the image: row shuffling, column shuffling, cyclic rotation of all the rows and cyclic rotation of all the columns. This stage reduces the correlation significantly among neighboring pixels. The second stage performs circular rotation of pixel values twice by scanning the image horizontally and vertically. The amount of rotation is based on $M{\times}N$ chaotic values. The last stage performs the diffusion four times by scanning the image in four different ways: block of $8{\times}8$ pixels, block of $16{\times}16$ pixels, principal diagonally, and secondary diagonally. Each of the above four diffusions performs the diffusion in two directions (forwards and backwards) with two previously diffused pixels and two chaotic values. This stage makes the scheme resistant to differential attacks. The security and performance of the proposed method is analyzed systematically by using the key space, entropy, statistical, differential and performance analysis. The experimental results confirm that the proposed method is computationally efficient with high security.

• The Journal of the Korea institute of electronic communication sciences
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• v.12 no.5
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• pp.747-754
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• 2017

Chaos-based secure communication systems are alternative of standard spread-spectrum systems that enable spreading the spectrum of the information signals and encrypting information signals with simple and inexpensive chaotic circuitry. In secure communication area, like Lorenz, Chua, Rossler, Duffing etc, classical systems are widely used. Malasoma chaotic system is topologically simple but their dynamical behaviors are non-linear synchronization and secure communication applications has not seen in paper. This paper aims for introducing a new chaotic system which is able to use as alternative to classical chaotic systems into secure communication fields. In addition, this new model simulates a synchronous communication system using P-C (Pecora-Carroll) method by verifying security with chaos signal through simulation. Modelling, synchronization and secure communication applications of Malasoma are realized respectively in MATLAB-Simulink environment. Retrieved results show that this novel chaotic system is able to use in secure communication fields.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.5
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• pp.565-570
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• 2015

Spread spectrum communications have increased interest due to their immunity to channel fading and low probability of intercept. One of the limitations of the traditional digital spread spectrum systems is the need for spreading code synchronization. Chaotic communication is the analogue alternative of digital spread spectrum systems beside some extra features like simple transceiver structures. In this paper, This paper was used instead of the digital modulation and demodulation carriers for use in the chaotic signal in a digital communication system among the chaotic modulation schemes, the Differential Chaos Shift Keying(DCSK) is the most efficient one because its demodulator detects the data without the need to chaotic signal phase recovery. Also Implementation of Differential Chaos Shift Keying Communication System Using Matlab/Simulink and the receiver con decode the binary information sent by the transmitter, performance curves of DCSK are given in terms of bit-error probability versus signal to noise ratio with spreading factor as a parameter and we compare it to BPSK modulation.

• Annals of Clinical Neurophysiology
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• v.3 no.1
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• pp.31-36
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• 2001

Background & Objectives : Fractal Dimension(FD) could be an index of correlation between variable parameters in non-linear chaotic signals. We tried to demonstrate that EEG wave is compatible with chaotic waves by measuring the Lyapunov exponent index and compared the difference of FD between variable age groups(teens, 30's, 50's) Methods : We estimated the Lyapunov exponent index and the FD from digital EEG data among five persons in each normal age groups by using the software which is programmed in our laboratory. Statistical analysis was done with SPSS win 8.0. The statistical differences of Lyapunov exponent index and FD between each electrodes and each age groups were done with ANOVA and paired sample t-test. Result : The Lyapunov exponent indexes were larger than 1 in each electrode and age group. There is no statistical difference in FD between each electrodes and each age groups. Except in 30th age group. In this group the FD of right hemisphere is larger than that of left hemisphere. Conclusion : The result of Lyapunov exponent index means EEG wave is a non-linear chaotic signal. And the results of FD suggest that chaotic parameters of right hemisphere is larger than those of left hemisphere at rest at least in younger people. We think that chaotic parameters can be a useful tool in investigating the variable diseases or brain states.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.39 no.1
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• pp.51-65
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• 2002

This paper presents a design method of the neural network-based controller using an indirect adaptive control method to deal with an intelligent control for chaotic nonlinear systems. The proposed control method includes the identification and control Process for chaotic nonlinear systems. The identification process for chaotic nonlinear systems is an off-line process which utilizes the serial-parallel structure of multilayer neural networks and simple state space neural networks. The control process is an on-line process which uses the trained neural networks as the system model. An error back-propagation method was used for training of identification and control for chaotic nonlinear systems. The performance of the proposed neural network controller was evaluated by application to the Duffing equation and the Lorenz equation, and the proposed controller was compared with other neural network-based controllers by computer simulations.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.485-490
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• 2003

In this paper, we propose the possibility of introducing chaotic sequences into digital watermarking systems as potential substitutes to commonly used pseudo noise sequences. Chaotic sequences have several good properties including the availability of a great number of them, the ease of their generation, as well as their sensitive dependence on their initial conditions. And the quantization does not destroy the good property. So this paper proposes a method that transforms Hangul text to chaotic sequence. And we presents how the Hangul text is expressed by an implied data and the implied data is regenerated into the original text. In this paper, we use this implied Hangul text for watermarking.

• 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.

• The Journal of Information Technology and Database
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• v.6 no.1
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• pp.73-88
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• 1999

There have been a series of debates to determine whether it would be possible to forecast dynamic systems such as stock markets. Recently the introduction of chaos theory has allowed many researchers to bring back this issue. Their main concern was whether the behavior of stock markets is chaotic or not. These studies, however, present divergent opinions on this question, depending upon the method applied and the data used. And the issue of predictability based on the nonlinear, chaotic nature was not dealt extensively. This paper is to test the nonlinear nature of the Korea stock market and accordingly attempts to predict its behavior. The result indicates that our stock market represents a chaotic behavior. We also found out based on our simulation that executing buy/sell transactions based upon forecasts which were derived using the local approximation method outperforms the decision of holding without a buy/sell transaction.