• 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.

• Journal of electromagnetic engineering and science
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• 제7권1호
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• pp.12-16
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• 2007

A UHF band wireless identification system based on passive surface acoustic wave(SAW) devices is presented in this paper. SAW ID tags were fabricated on Y-Z $LiNbO_3$ piezoelectric substrate with a good electro-mechanical coupling property. To reduce degradation of the antenna performance associated with the piezoelectric materials, an efficient design of the SAW RFID antenna is introduced. By measuring the parameters of the SAW ID tag, the performance of the antenna was tested by experimentation.

• Journal of Electrical Engineering and Technology
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• 제4권1호
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• pp.135-142
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• 2009

In this paper the Simplified Refined Instrumental Variable (SRIV) identification algorithm for SISO systems is extended to MIMO systems described by a Left Matrix Fraction Description (LMFD). The performance of the extended algorithm is compared to the well-known MIMO four-step instrumental variable (IV4) algorithm. Monte Carlo simulations for different signal to noise ratios are conducted to assess the performance of the algorithm. Moreover, the algorithm is applied to a simulated quadruple tank process.

• 한국항행학회논문지
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• 제22권4호
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• pp.288-294
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• 2018

항공기의 엔터테인먼트 시스템은 고정된 모니터를 사용하는 대신에 승객 개인의 휴대용 전자기기를 사용하는 형태로 그 패러다임이 바뀌었다. 이로 인해 기내 설비는 간소해진 반면 휴대용 전자기기들의 전기 충전으로 안전에 대한 리스크는 증가되었다. 송신 기능이 없는 개인 휴대전자기기와 달리 와이파이 기능이 있는 전자기기(T-PED)의 사용이 허용되고 기내에서 배터리의 충전도 요구된다. 본 연구에서는 기내 무선 환경과 엔터테인먼트 서비스의 변화에 따른 영향을 조사하기 위해 NASA 항공안전보고시스템을 이용하여 기내 전자기기 사용 관련 자료를 분석하였다. 이를 기초로 하여, 항공기 안전관리 관점에서 비행 중에 발생된 객실 전자장비나 승객 휴대용 전자기기(특히 스마트폰)로 인한 이벤트 발생 사례를 공유하여 개인용 전자기기의 위험성을 분석하였다. 이러한 분석을 위해 잠재적 위해요인의 식별과 리스크 평가 작업이 수행되었으며, 최종적으로 휴대용 전자기기의 안전한 사용을 위한 리스크 완화 전략이 제시되었다.

• 전기전자학회논문지
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• 제19권4호
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• pp.610-616
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• 2015

본 논문에서는 지문 인식을 이용하여 공인인증서의 보안 조건을 만족하는 전자 신분증 시스템을 설계 및 개발하였다. 제안하는 전자 신분증 시스템은 지문 정보를 사용하여 위변조 불가, 기밀성, 무결성, 본인 인증 (=부인 방지)등의 기능을 가진 전자서명문을 생성하고, 이를 암호화, 전송 및 검증한다. 제안하는 전자 신분증 시스템은 사용자 암호 대신에 지문을 사용하여 유출 및 탈취를 피하면서도 기존의 공인인증서와 동일한 법적 효력을 가진다. 제안하는 전자 신분증 시스템은 HSM 디바이스, 검증 서버, CA 서버, RA 클라이언트의 4개 모듈로 설계하였으며 각 모듈의 프로토타입이 정상적으로 동작하는 것을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.285-288
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• 1998

A least-squares identification method is studied that estimates a finite number of coefficients in the series expansion of a transfer function, where the expansion is in terms of recently introduced generalized basis functions, We will expand and generalize the orthogonal functions as basis functions for dynamical system representations. To this end, use is made of balanced realizations as inner transfer functions. The orthogonal functions can be considered as generalizations of, for example, the pulse functions, Laguerre functions, and Kautz functions, and give rise to an alternative series expansion of rational transfer functions. We show that the Laplace transform of the expansion for some sets$\Psi_{\kappa}(Z)$ is equivalent to a series expansion . Techniques based on this result are presented for obtaining the coefficients $c_{n}$ as those of a series. One of their important properties is that, if chosen properly, they can substantially increase the speed of convergence of the series expansion. This leads to accurate approximate models with only a few coefficients to be estimated. The set of Kautz functions is discussed in detail and, using the power-series equivalence, the truncation error is obtained.

• 센서학회지
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• 제20권3호
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• pp.151-155
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• 2011

A variety of pattern recognition algorithms including neural networks may be applicable to the identification of odors. In this paper, an identification technique for an electronic odor sensing system applicable to wound state monitoring is presented. The performance of the radial basis function(RBF) network is highly dependent on the choice of centers and widths in basis function. For the fine tuning of centers and widths, those parameters are initialized by an ill-conditioned genetic fuzzy c-means algorithm, and the distribution of input patterns in the very first stage, the stochastic gradient(SG), is adapted. The adaptive RBF network with singular value decomposition(SVD), which provides additional adaptation capabilities to the RBF network, is used to process data from array-based gas sensors for early detection of wound infection in burn patients. The primary results indicate that infected patients can be distinguished from uninfected patients.

• Journal of Electrical Engineering and Technology
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• 제11권3호
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• pp.769-774
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• 2016

In the design of sensorless control system for induction motor, high-precision speed estimation is one of the most difficult problems. To solve this problem, the common method is model reference adaptive method (MRAS). MRAS requires accurate motor parameters to estimate rotor speed precisely. However, when motor is running, the variety of temperature and magnetic saturation will lead to the change of motor parameters such as stator resistance and rotor resistance, which will lower the accuracy of the speed estimation. To improve the accuracy and rapidity of speed estimation, this paper analyses the mutual MRAS speed identification based on rotor flux linkage, and proposes an improved mutual MRAS speed identification based on back-EMF. The improved method is verified by Simulink simulation and motor experimental platform based on DSP2812. The results of simulation and experiment indicate that the method proposed by this paper can significantly improve the accuracy of speed identification, and speed up the response of identification.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제5권1호
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• pp.76-82
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• 2005

Speech signal has various features of speakers. This feature is extracted from speech signal processing. The speaker is identified by the speaker identification system. In this paper, we propose the speaker identification system that uses the incremental learning based on neural network. Recorded speech signal through the microphone is blocked to the frame of 1024 speech samples. Energy is divided speech signal to voiced signal and unvoiced signal. The extracted 12 orders LPC cpestrum coefficients are used with input data for neural network. The speakers are identified with the speaker identification system using the neural network. The neural network has the structure of MLP which consists of 12 input nodes, 8 hidden nodes, and 4 output nodes. The number of output node means the identified speakers. The first output node is excited to the first speaker. Incremental learning begins when the new speaker is identified. Incremental learning is the learning algorithm that already learned weights are remembered and only the new weights that are created as adding new speaker are trained. It is learning algorithm that overcomes the fault of neural network. The neural network repeats the learning when the new speaker is entered to it. The architecture of neural network is extended with the number of speakers. Therefore, this system can learn without the restricted number of speakers.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2003년도 ISIS 2003
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• pp.322-325
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• 2003

In this paper, we propose n new fuzzy model identification of time series system using wavelet transform and genetic DNA code. Generally, it is well known that the DNA coding method is more diverse in the knowledge expression and better in the optimization performance than the genetic algorithm (GA) because it can encode more plentiful genetic information based on the biological DNA. The proposed method can construct a fuzzy model using the wavelet transform, in which the coefficients are identified by the DNA coding method. Thus, we can effectively get the fuzzy model of the nonlinear system by using the advantages of both wavelet transform and DNA coding method. In order to demonstrate the superiority of the proposed method, it is compared with modeling method using the conventional GA.