• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 춘계종합학술대회 A
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• pp.768-771
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• 2008

컴퓨터를 활용한 제어 기술이 발달함에 따라 무인화 시스템이 증가하고 있는 현실이다. 이 논문에서는 현재 많은 연구가 활발히 이루어지고 있는 무인화 시스템들 중의 하나인 무인 자동 주차 시스템을 위한 기법을 제안하고 시뮬레이션 실험을 통하여 그 가능성을 보였다. 제안한 자동 주차 시스템에서는 센서 정보를 입력으로 하고 퍼지 함수에 의한 추론 결과를 활용하여 조향 장치를 제어하는 방식을 제안하였다. 성능 평가를 위하여 그래픽 시뮬레이션 환경을 구축하고 제안한 기법을 이용한 가상자동차의 주차 과정을 보였으며 그 결과를 분석하였다.

• 한국정보통신학회:학술대회논문집
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• 한국해양정보통신학회 2008년도 춘계종합학술대회 A
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• pp.429-432
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• 2008

의료서비스 분야에서 유비궈터스 IT 기술과 헬스케어 기술을 접목함으로써 일상생활 중 지속적으로 건강상태를 모니터링하여 항상 건강한 상태의 유지가 가능하도록 하는 유비쿼터스 헬스케어기술이 급부상하고 있다. 본 연구에서는 유비쿼터스 헬스케어와 관련하여 일상생활 중 활동 상태에 따른 가속도 변화를 측정하여 활동 상태를 판단하고 활동량을 정량화하기 위한 지표를 개발하고자 하였다. 먼저 활동상태에 따른 가속도 정보를 측정하기 위해 단일침의 3축가속도 센서를 사용하였으며, 아날로그 가속도신호를 디지털로 변환하고 데이터의 무선전송을 위해 무선센서네트워크 기술을 적용한 센서노드를 활용하였다. 그리고 무선으로 전송된 가속도 신호를 PC또는 휴대형 단말기에서 모니터링하기 위해 모니터링 프로그램을 구현하였다. 계측된 가속도 신호로부터 활동상태의 분류 및 활동량의 정량화를 위한 방법을 제시하고 그 타당성을 평가하였다.

• 말소리와 음성과학
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• 제1권2호
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• pp.3-8
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• 2009

In an effort to improve speech recognition, we investigated the effect of the number of clusters. In usual LBG clustering, the number of codebook clusters is doubled on each bifurcation and hence cannot be chosen arbitrarily in a natural way. To have the number of clusters at our control, we combined adaptive resonance theory (ART2) with LBG and perform the clustering in two stages. The codebook thus formed was used in subsequent processing of fuzzy vector quantization (FVQ) and HMM for speech recognition tests. Compared to conventional LBG, our method was shown to reduce the best recognition error rate by 0${\sim$}0.9% depending on the vocabulary size. The result also showed that between 400 and 800 would be the optimal number of clusters in the limit of small and large vocabulary speech recognitions of isolated words, respectively.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제16권2호
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• pp.140-146
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• 2016

This paper proposes a control method of the Segway with unknown control coefficient and input saturation. To design a simple controller for the Segway with the model uncertainty, the prescribed performance function is used. Furthermore, an auxiliary variable is introduced to deal with unknown time-varying control coefficient and input saturation problem. Due to the auxiliary variable, function approximators are not used in this paper although all model uncertainties are unknown. Thus, the controller can be simple. From the Lyapunov stability theory, it is proved that all errors of the proposed control system remain within the prescribed performance bounds. Finally, the simulation results are presented to demonstrate the performance of the proposed scheme.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권3호
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• pp.143-148
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• 2011

In this paper, a backstepping design is proposed to achieve stabilization and synchronization for the Lorenz-Stenflo (LS) chaotic system. The proposed method is a recursive Lyapunov-based scheme and provides a systematic procedure to design stabilizing controllers. The proposed controller enables stabilization of the chaotic motion and synchronization of two identical LS chaotic systems using only a single control input. Numerical simulations are presented to validate the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제11권4호
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• pp.293-298
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• 2011

In this paper, we propose a new image descriptor, that is, a rotation invariant histogram of oriented gradients (RIHOG). RIHOG overcomes a disadvantage of the histogram of oriented gradients (HOG), which is very sensitive to image rotation. The HOG only uses magnitude values of a pixel without considering neighboring pixels. The RIHOG uses the accumulated relative magnitude values of corresponding relative orientation calculated with neighboring pixels, which has an effect on reducing the sensitivity to image rotation. The performance of RIHOG is verified via the index of classification and classification of Brodatz texture data.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권1호
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• pp.1-11
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• 2013

The determination of the pose of the imaging camera is a fundamental problem in computer vision. In the monocular case, difficulties in determining the scene scale and the limitation to bearing-only measurements increase the difficulty in estimating camera pose accurately. Many mobile phones now contain inertial measurement devices, which may lend some aid to the task of determining camera pose. In this study, by means of simulation and real-world experimentation, we explore an approach to monocular camera localization that incorporates both observations of the environment and measurements from accelerometers and gyroscopes. The unscented Kalman filter was implemented for this task. Our main contribution is a novel approach to landmark initialization in a Kalman filter; we characterize the tolerance to noise that this approach allows.

• Journal of information and communication convergence engineering
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• 제6권4호
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• pp.444-447
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• 2008

In this paper, we proposed the recognition system of car license plates to mitigate traffic problems. The processing sequence of the proposed algorithm is as follows. At first, a license plate segment is extracted from an acquired car image using morphological features and color information, and noises are eliminated from the extracted license plate segment using line scan algorithm and Grassfire algorithm, and then individual codes are extracted from the license plate segment using edge tracking algorithm. Finally the extracted individual codes are recognized by an FCM algorithm. In order to evaluate performance of segment extraction and code recognition of the proposed method, we used 100 car images for experiment. In the results, we could verify the proposed method is more effective and recognition performance is improved in comparison with conventional car license plate recognition methods.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.104-112
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• 2001

Simply, Nonlinear dynamics theory means the complicated and noise-like phenomena originated form nonlinearity involved in deterministic dynamical system. An almost all the natural signals have nonlinear property. However, there exist few analysis software tool or package for a research and development of applications. We develop nonlinear time series analysis simulator is to provide a common and useful tool for this purpose and to promote research and development of nonlinear dynamics theory. This simulator is consists of the following four modules such as generation module, preprocessing module, analysis module and ICA module. In this paper, we applied to Electroencephalograph (EEG), as it turned out, our simulator is able to analyze nonlinear time series. Besides, we could get the useful results using the various parameters. These results are used to diagnostic the brain diseases.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제6권2호
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• pp.110-115
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• 2006

In pure P2P environment, it is possible to provide service by using a little real-time information without using accumulated information. But in case of using only a little information that was locally collected, quality of recommendation service can be fallen-off. Therefore, it is necessary to study a method to improve qualify of recommendation service by using users' context information. But because a great volume of users' context information can be recognized in a moment, there can be a scalability problem and there are limitations in supporting differentiated services according to fields and items. In this paper, we solved the scalability problem by clustering context information per each service field and classifying it per each user, using SOM. In addition, we could recommend proper services for users by quantifying the context information of the users belonging to the similar classification to the service requester among classified data and then using collaborative filtering.