• 전자공학회논문지S
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• 제34S권4호
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• pp.57-65
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• 1997

The purpose of this paper is to propose the HMM (hidden markov model) based on multi-observation sequence for the isolated word recognition. The proosed model generates the codebook of MSVQ by dividing each word into several sections followed by dividing training data into several sections. Then, we are to obtain the sequential value of multi-observation per each section by weighting the vectors of distance form lower values to higher ones. Thereafter, this the sequential with high probability value while in recognition. 146 DDD area names are selected as the vocabularies for the target recognition, and 10LPC cepstrum coefficients are used as the feature parameters. Besides the speech recognition experiments by way of the proposed model, for the comparison with it, the experiments by DP, MSVQ, and genral HMM are made with the same data under the same condition. The experiment results have shown that HMM based on multi-observation sequence proposed in this paper is proved superior to any other methods such as the ones using DP, MSVQ and general HMM models in recognition rate and time.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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• pp.348-353
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems arc represented by fuzzy models since fuzzy logic systems arc universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• 한국신뢰성학회지:신뢰성응용연구
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• 제3권2호
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• pp.127-136
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• 2003

This paper investigates the effect of individual observations in regression models with MA(1) errors through the 'hat matrix' It shows that the first observation has the largest hat matrix diagonal component for $\theta$＜0 in the regression model with an intercept. This provides additional evidence for retaining the first observation in performing estimation in this setting. When the regression model goes to the origin and the independent variable has a deterministic trend, the last observation has the greatest leverage for │$\theta$│＜1 and may have potentially large impact on parameter estimation.

• 인터넷정보학회논문지
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• 제17권3호
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• pp.25-32
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• 2016

본 논문에서는 에지를 사용한 관측 모델과 파티클 필터를 이용하여 실시간으로 객체를 추적하는 방법을 제안한다. 논문에서 제안하는 방법은 먼저, 초기 프레임에서 추적하고자 하는 객체를 지정한다. 지정된 객체에 대해 에지 관측 모델과 N개의 파티클 필터 집합을 생성한다. 에지 관측 모델과 파티클의 8방향 에지 모델의 중간 거리 평균을 비교하여 가중치를 계산하고, 계산된 값으로 가중치를 업데이트한다. 업데이트된 가중치를 이용해 파티클들을 리샘플링한 후, 추적 객체의 상태인 현재 위치를 추정할 수 있다. 마지막으로 본 논문에서 제안하는 방법은 여러 실험 데이터를 이용하여 기존의 방법과의 비교분석을 통해 안정적인 추적에 대한 성능을 입증한다.

• 대한조선학회논문집
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• 제46권6호
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• pp.569-577
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• 2009

As the scale factor of model propellers utilized in cavitation test is about 40, it is difficult to find out practical countermeasures against the small area erosions on the blade tip region throughout model erosion tests. In this study, a partial propeller blade model was used for the observation of cavitation pattern for the eroded propeller. A partial propeller blade model was manufactured from 0.7R to tip with expanded profile and with adjustable device of angle of attack. Reynold's number of a partial propeller blade model is 7 times larger than that of a model propeller. Also, anti-singing edge and application of countermeasures to partial propeller blade model which produced in large scale can be more practical than a model propeller. For the observation of cavitation at high Reynold's number, high speed cavitation tunnel was used. To find out the most severe erosive blade position during a revolution, cavitation observation tests were carried out at 5 blade angle positions.

• Communications for Statistical Applications and Methods
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• 제6권3호
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• pp.667-676
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• 1999

We investigate the effects of omission of initial observations in each individuals in the panel data regression model when the disturbances follow a serially correlated one way error components. We show that the first transformed observation can have a relative large hat matrix diagonal component and a large influence on parameter estimates when the correlation coefficient is large in absolute value.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.192-196
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• 한국지능시스템학회논문지
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• 제14권7호
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• pp.927-933
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• 2004

This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

• 한국농공학회논문집
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• 제61권2호
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• pp.63-74
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• 2019

The objective of this study was to evaluate the influence of rainfall observation network on daily dam inflow using artificial neural networks(ANNs). Chungju Dam and Soyangriver Dam were selected for the study watershed. Rainfall and dam inflow data were collected as input data for construction of ANNs models. Five ANNs models, represented by Model 1 (In watershed, point rainfall), Model 2 (All in the Thiessen network, point rainfall), Model 3 (Out of watershed in the Thiessen network, point rainfall), Model 1-T (In watershed, area mean rainfall), Model 2-T (All in the Thiessen network, area mean rainfall), were adopted to evaluate the influence of rainfall observation network. As a result of the study, the models that used all station in the Thiessen network performed better than the models that used station only in the watershed or out of the watershed. The models that used point rainfall data performed better than the models that used area mean rainfall. Model 2 achieved the highest level of performance. The model performance for the ANNs model 2 in Chungju dam resulted in the $R^2$ value of 0.94, NSE of 0.94 $NSE_{ln}$ of 0.88 and PBIAS of -0.04 respectively. The model-2 predictions of Soyangriver Dam with the $R^2$ and NSE values greater than 0.94 were reasonably well agreed with the observations. The results of this study are expected to be used as a reference for rainfall data utilization in forecasting dam inflow using artificial neural networks.

• 로봇학회논문지
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• 제7권1호
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• pp.29-34
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• 2012

This paper suggests a new observation model for Extended Kalman Filter based Simultaneous Localization and Mapping (EKF-SLAM). Since the EKF framework linearizes non-linear functions around the current estimate, the conventional line model has large linearization errors when a mobile robot locates faraway from its initial position. On the other hand, the model that we propose yields less linearization error with respect to the landmark position and thus suitable in a large-scale environment. To achieve it, we build up a three-dimensional space by adding a virtual axis to the robot's two-dimensional coordinate system and extract a plane by using a detected line on the two-dimensional space and the virtual axis. Since Jacobian matrix with respect to the landmark position has small value, we can estimate the position of landmarks better than the conventional line model. The simulation results verify that the new model yields less linearization errors than the conventional line model.