• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1998년도 추계종합학술대회 논문집
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• pp.1297-1300
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• 1998

In this paper, we discuss the identification of a chaotic system using chaotic neural networks. Because of selfconnections in neuron itself and interconnections between neurons, chaotic neural networks identifiers show good performance in highly nonlinear dynamics such as chaotic system. Simulation results are presented to demonstrate robustness of chaotic neural networks identifier.

• 한국전자파학회논문지
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• 제19권3호
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• pp.384-390
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• 2008

본 논문에서는 TSMC 0.18 um CMOS 공정을 사용하여 UWB Chaotic-OOK(On-Off Keying) 통신을 위한 송신기를 설계하였다. 송신기는 Quasi-chaotic 신호 발생기, OOK 변조기, 구동 증폭기로 구성되어 있다. 일반적으로 아날로그 피드백을 사용하는 chaotic 신호 발생기는 공정 변화에 대한 취약점이 있어 이를 개선하기 위하여 디지털 피드백 구조의 Quasi-chaotic 신호 발생기를 사용하였다 또한, OOK 변조를 위해 T형 구조의 변조기와 단일 출력 신호를 얻기 위한 차동 입력 단일 출력 구동 증폭기를 설계하였다. 측정 결과, 요구되는 spectrum mask를 만족시키는 출력을 얻었으며, 데이터 20 Kbps, 200 Kbps, 2 Mbps, 10 Mbps에 따른 OOK 변조 테스트를 통해 출력 신호를 확인하여 UWB chaotic-OOk 송신기로 사용 가능함을 확인하였다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 1999년도 하계종합학술대회 논문집
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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.

• Kyungpook Mathematical Journal
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• 제55권3호
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• pp.563-586
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• 2015

In this research work, a seven-term 3-D novel jerk chaotic system with two quadratic nonlinearities has been proposed. The basic qualitative properties of the novel jerk chaotic system have been described in detail. Next, an adaptive backstepping controller is designed to stabilize the novel jerk chaotic system with two unknown parameters. Moreover, an adaptive backstepping controller is designed to achieve complete chaos synchronization of the identical novel jerk chaotic systems with two unknown parameters. MATLAB simulations have been shown in detail to illustrate all the main results developed for the 3-D novel jerk chaotic system.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제7권4호
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• pp.236-241
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• 2007

This paper presents an adaptive controller using chaotic dynamic neural networks(CDNN) for nonlinear dynamic system. A new dynamic backpropagation learning method of the proposed chaotic dynamic neural networks is developed for efficient learning, and this learning method includes the convergence for improving the stability of chaotic neural networks. The proposed CDNN is applied to the system identification of chaotic system and the adaptive controller. The simulation results show good performances in the identification of Lorenz equation and the adaptive control of nonlinear system, since the CDNN has the fast learning characteristics and the robust adaptability to nonlinear dynamic system.

• 한국산학기술학회논문지
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• 제13권1호
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• pp.311-316
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• 2012

본 논문에서는 공학적 응용을 위한 로렌츠 카오스 시스템을 연산증폭기, 곱셈기 등을 이용하여 전자회로로 설계하였다. 시간파형, 위상특성 등 여러 가지 카오스 동적특성 등을 PSPICE 모의실험을 통하여 파악하였다. 저항값의 변화를 통하여 카오스 특성을 얻기 위한 최적화 된 회로 파라미터를 구하였으며, 각 저항값의 변화에 따른 시간파형 특성 및 위상 특성을 구하였다.

• Wind and Structures
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• 제36권3호
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• pp.215-220
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• 2023

We study the progressive full-scale wind tunnel tests on a high solidity vertical axis wind turbine (VAWT) for various tip speeds and pitch angles to understand the VAWT shaft system's dynamics using 0-1 Test for chaos. We identify that while varying rotor speed (tip speed) of the turbine, the system's dynamics change from periodic to chaotic through quasiperiodic and strange non-chaotic (SNA) states. The present study is the first experimental evidence for the existence of these states in the VAWT shaft system to the best of our knowledge. Using the asymptotic growth value Kc in 0-1 test, when the turbine operates at the low tip speeds and high pitch angles for low incoming wind speeds, the system behaves periodic (Kc ≈ 0). However, when the incoming wind speed increases further the system's dynamics shift from periodic to chaotic vibrations through quasi-periodic and SNA. This phenomenon is due to the dynamic stalling of blades which induces chaotic vibration in the VAWT shaft system. Further, the singular continuous spectrum method validates the presence of SNA and differentiates the SNA from chaotic vibrations.

• 한국정보기술응용학회:학술대회논문집
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• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
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• pp.339-342
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• 2005

In order to support ultrawide-band signal generation for low rate WPAN, several types of signal generation mechanisms are suggested such as Chaos, Impluse, and Chirp signals by the activity of IEEE 802.15.4a. The communication system applied chaos theory may have ultrawide-band characteristics with spread spectrum and immunity from multipath effect. In order to use the advantage of chaotic signal generation, we introduce the system implementation of communication and networking systems with the chaos UWB signal. This system may be composed of mainly three parts in hardware architecture : RF transmission with chaotic signal generation, signal receiver using amplifiers and filters, and 8051 & FPGA unit. The most difficult part is to implement the chaotic signal generator and build transceiver with it. The implementation of the system is devidced into two parts i.e. RF blocks and digital blocks with amplifiers, filters, ADC, 8051 processor, and FPGA. In this paper, we introduce the system block diagram for chaotic communications. Mainly the RF block is important for the system to have good performance based on the chaotic signal generator. And the main control board functions for controlling RF blocks, processing Tx and Rx data, and networking in MAC layer.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 추계학술대회 논문집 학회본부 D
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• pp.621-623
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• 2000

In this paper, the effective design method of the predictive controller using fuzzy neural networks(FNNs) is presented for the Intelligent control of chaotic nonlinear systems. In our design method of controller, predictor parameters are tuned by the error value between the actual output of a chaotic nonlinear system and that of a fuzzy neural network model. And the parameters of predictive controller using fuzzy neural network are tuned by the gradient descent method which uses control error value between the actual output of a chaotic nonlinear system and the reference signal. In order to evaluate the performance of our controller, it is applied to the Duffing system which are the representative continuous-time chaotic nonlinear systems and the Henon system which are representative discrete-time chaotic nonlinear systems.

• 한국통신학회논문지
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• 제32권11A호
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• pp.1138-1145
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• 2007

In wireless communications, chaotic communications have been a field of interest due to its low complexity in hardware implementation and low power consumption in chaotic signal generation. Among the modulation schemes using the chaotic signal, Differential Chaos Shift Keying (DCSK) is a robust non coherent technique. As in the conventional communication systems, chaos-based systems are required to provide reasonable bit error performance in the presence of a narrow-band signal coming from any other systems. The frequency band of this foreign narrow band signal may lie within the bandwidth of the chaos-based systems. This situation may occur when chaotic signal transmission is done in the presence of other conventional communication system. This paper has evaluated the performance of the non coherent differential chaos shift keying (DCSK) system under the presence of conventional non-chaotic transmit reference system. Both systems are assumed to have same data rates. The mathematical expressions for the bit error rate (BER) are derived with computer simulations to verify the analytical results.