• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.3976-3982
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• 2013

This paper presents a temperature analysis of the chaotic behavior in the voltage controlled CMOS chaotic circuit. The circuit is based on a simple nonlinear function block which is needed for chaotic signal generation. It consists of a NFB (nonlinear function block), a level shifter and non-overlapping two-phase clock for sample and hold. By SPICE simulation, chaotic dynamics such as frequency spectra and bifurcations according to the temperature variations were analyzed. And, it was showed that the circuit can generate discrete chaotic signals within control voltage in the range from 1.2 V to 2.3 V in a specific temperature condition of $25^{\circ}C$.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.578-580
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• 1995

In this paper, a method for the daily maximum load forecasting which uses a chaotic time series in power system and artificial neural network. We find the characteristics of chaos in power load curve and then determine a optimal embedding dimension and delay time, For the load forecast of one day ahead daily maximum power, we use the time series load data obtained in previous year. By using of embedding dimension and delay time, we construct a strange attractor in pseudo phase plane and the artificial neural network model trained with the attractor font mentioned above. The one day ahead forecast errors are about 1.4% of absolute percentage average error.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.835-837
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• 1996

In this paper, a method for the daily maximum load forecasting which uses a chaotic time series in power system and artificial neural network(Back-propagation) is proposed. We find the characteristics of chaos in power load curve and then determine a optimal embedding dimension and delay time. For the load forecast of one day ahead daily maximum power, we use the time series load data obtained in previous year. By using of embedding dimension and delay time, we construct a strange attractor in pseudo phase plane and the artificial neural network model trained with the attractor mentioned above. The one day ahead forecast errors are about 1.4% for absolute percentage average error.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.91-97
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• 2014

Chaotic dynamics is an active research area in fields such as biology, physics, sociology, psychology, physiology, and engineering. Interest in chaos is also expanding to the social sciences, such as politics, economics, and societal events prediction. Most people pursue happiness, both spiritual and physical in many cases. However, happiness is not easy to define, because people differ in how they perceive it. Happiness can exist in mind and body. Therefore, we need to be happy in both simultaneously to achieve optimal happiness. To do this, we need to synchronize mind and body. In this paper, we propose a chaotic synchronization method in a mathematical model of happiness organized by a second-order ordinary differential equation with external force. This proposed mathematical happiness equation is similar to Duffing's equation, because it is derived from that equation. We introduce synchronization method from our mathematical happiness model by using the derived Duffing equation. To achieve chaotic synchronization between the human mind and body, we apply an idea of mind/body unity originating in Oriental philosophy. Of many chaotic synchronization methods, we use only coupled synchronization, because this method is closest to representing mind/body unity. Typically, coupled synchronization can be applied only to non-autonomous systems, such as a modified Duffing system. We represent the result of synchronization using a differential time series mind/body model.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.35C no.12
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• pp.77-84
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• 1998

A voltage controlled chaotic circuit has been designed in integrated circuit and fabricated by using 0.8$\mu\textrm{m}$ single poly CMOS technology. The fabricated chaotic circuit consist of sample and hold circuits, op-amps, nonlinear function generator and two phase clock generator. The test results of the chaotic circuit show that periodic state, quasi-periodic state and chaotic state can be obtained according to the input control voltage with the ${\pm}$2.5V power supply and clock rate of 20kHz. In addition, two dimensional chaotic patterns have been observed by connecting this circuit in parallel or series

• Steel and Composite Structures
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• v.49 no.6
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• pp.701-711
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• 2023

In order to fully reflect variation characteristics of composite concrete dam health state, the monitoring data is applied to diagnose composite concrete dam health state. Composite concrete dam lesion development to wreckage is a precursor, and its health status can be judged. The monitoring data are generally non-linear and unsteady time series, which contain chaotic information that cannot be characterized. Thus, it could generate huge influence for the construction of monitoring models and the formulation of corresponding health diagnostic indicators. This multi-scale diagnosis process is from point to whole. Chaotic characteristics are often contained in the monitoring data. If chaotic characteristics could be extracted for reflecting concrete dam health state and the corresponding diagnostic indicators will be formulated, the theory and method of diagnosing concrete dam health state can be huge improved. Therefore, the chaotic characteristics of monitoring data are considered. And, the extracting method of the chaotic components is studied from monitoring data based on fuzzy dynamic cross-correlation factor method. Finally, a method is proposed for formulating composite concrete dam health state indicators. This method can effectively distinguish chaotic systems from deterministic systems and reflect the health state of concrete dam in service.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2003.10a
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• pp.589-593
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• 2003

In this paper, we propose that the chaotic behavior analysis in the mobile robot of embedding Chua's equation with obstacle. In order to analysis of chaotic behavior in the mobile robot, we apply not only qualitative analysis such as time-series, embedding phase plane, but also quantitative analysis such as Lyapunov exponent in the mobile robot with obstacle. In the obstacle, we only assume that all obstacles in the chaos trajectory surface in which robot workspace has an unstable limit cycle with Van der Pol equation.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.7
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• pp.1414-1420
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• 1994

In this paper the existence of chaotic signal is probed in adaptive dead beat control law for nonlinear dynamic system. These chaotic signal makes the system unstable and difficult to control, but it broaden the range of application, confirms the robustness of system and gives a lot of information. Considering of low correlation between chaotic signals, robust adaptive control method which uses for parameter estimation is proposed. With this algorithm the parameters converges stable rapidly. Finally the superiority of it is proved by computer simulation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.9 no.11
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• pp.4556-4572
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• 2015

Dynamic texture (DT) recognition is a challenging problem in numerous applications. In this study, we propose a new algorithm for DT recognition based on group sparsity structure in conjunction with chaotic feature vector. Bag-of-words model is used to represent each video as a histogram of the chaotic feature vector, which is proposed to capture self-similarity property of the pixel intensity series. The recognition problem is then cast to a group sparsity model, which can be efficiently optimized through alternating direction method of multiplier algorithm. Experimental results show that the proposed method exhibited the best performance among several well-known DT modeling techniques.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2004.05a
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• pp.123-127
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• 2004

In this paper, we propose that the chaotic behavior analysis in the several Arnold chaos mobile robot of embedding some chaotic such as Arnold equation with obstacle. In order to analysis of chaotic behavior in the mobile robot, we apply not only qualitative analysis such as time-series, embedding phase plane, but also quantitative analysis such as Lyapunov exponent in the mobile robot with obstacle. We consider that there are two type of obstacle, one is fixed obstacle and the other is hidden obstacle which have an unstable limit cycle. In the hidden obstacles case, we only assume that all obstacles in the chaos trajectory surface in which robot workspace has an unstable limit cycle with Van der Pol equation.