• ICROS
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• v.17 no.3
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• pp.22-26
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• 2011

신경회로망 기술은 다양한 공학적 및 과학적 문제에 적용되어 왔으며 복잡한 동특성을 갖는 시스템의 모델링에 특히 효율적인 것으로 알려져 있다. 신경회로망 학습은 신경회로망의 가중치 및 바이러스로서 주어지는 파라미터 벡터의 요소를 주어진 목적함수를 최소화하는 최적의 값으로 추정하는 연산과정을 의미한다. 따라서 신경회로망 파라미터 학습은 전체시스템의 성능을 직접적으로 좌우하는 매우 중요한 단계라 할 수 있으며 일반적으로 파라미터의 수정규칙 알고리즘을 도출한다. 이러한 수정규칙은 주로 최적화 기법을 적용하며 경사함수(gradient function)를 포함한다. 최근에는 이러한 경사함수를 포함하지 않는 학습 알고리즘이 많이 개발되고 있으며 특히 칼만 필터링 이론을 접목한 미분 신경회로망의 학습 알고리즘이 최근에 발표되었다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.10C
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• pp.1013-1022
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• 2003

This paper implemented the real-time object tracking algorithm that extracts and tracks the moving object adaptively to input frame sequence by using non-parametric image processing method and Kalman filter-based dynamic AR(2) process method. By applying non-parametric image processing to input frames, the moving object was extracted from the background adaptively to diverse environmental conditions. And the movement of object was able to be adaptively estimated and tracked by modeling the various movement of object as dynamic AR(2) process and estimating based on the Kalman filter the parameters of AR(2) process dynamically changing along time. The experiments of the implemented object tracking system showed that the proposed method tracked the moving object as more approximately as the estimation error became about l/2.5∼1/50 of one of the traditional tracking method based on linear Kalman filter.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.2
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• pp.438-446
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• 2013

Generally, a camera isn't located at the center of display in a tele-presence system and it causes an incorrect eye contact between speakers which reduce the realistic feeling during the conversation. To solve this incorrect eye contact problem, we newly propose an intermediate view reconstruction algorithm using both a color camera and a depth camera and applying for the depth image based rendering (DIBR) algorithm. In the proposed algorithm, an efficient hole filling method using the arithmetic mean value of neighbor pixels and an efficient boundary noise removal method by expanding the edge region of depth image are included. We show that the generated eye-contacted image has good quality through experiments.

• Journal of KIISE
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• v.42 no.6
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• pp.748-754
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• 2015

This paper proposes a sequential state estimation model consisting of continuous and discrete variables, as a way of generalizing all discrete-state factorial HMM, and gives a design of gait motion model based on the idea. The discrete state variable implements a Markov chain that models the gait dynamics, and for each state of the Markov chain, we created a Gaussian process over the space of the continuous variable. The Markov chain controls the switching among Gaussian processes, each of which models the rotation or various views of a gait state. Then a particle filter-based algorithm is presented to give an approximate filtering solution. Given an input vector sequence presented over time, this finds a trajectory that follows a Gaussian process and occasionally switches to another dynamically. Experimental results show that the proposed model can provide a very intuitive interpretation of video-based gait into a sequence of poses and a sequence of posture states.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.35 no.11
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• pp.1199-1204
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• 2011

The capability to bilaterally telemanipulate soft-tissues for medical applications could increase the quality of telemanipulation systems. Since most soft-tissue manipulation tasks include constrained motion interacting with an unknown and dynamic bioenvironment through contact, bilateral telemanipulation raises problems due to stability and transparency issues. It is well understood that knowledge of environments plays an important role in pursuing transparent telemanipulation and achieving telepresence, and in particular, online estimation of environmental parameters with an explicit environment model can improve these systems' performance. In this study, a continuum mechanics-based environment model with an online environmental property estimation algorithm and an adaptive telemanipulation control scheme is proposed. The proposed method can improve the telemanipulation performance in terms of stability and transparency and can offer valuable information (e.g., elastic modulus of soft tissues) pertaining to diagnostic examinations.

• Journal of Advanced Navigation Technology
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• v.21 no.1
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• pp.43-49
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• 2017

Generally, loop filter based scalar tracking loops (LF-STL) have been used for global positioning system (GPS) signal tracking algorithm. This paper introduces the accuracy and robustness of linear-quadratic-Gaussian based vector tracking loop (LQG-VTL) algorithm instead of LF-STL. To verify the accuracy of LQG-VTL, we confirm that the measurements estimation errors of the LQG based scalar tracking loops (LQG-STL) are improved by more than 60 % compared to LF-STL. Also, when LQG-VTL is used, measurements estimation errors decrease compared to LQG-STL, and position/velocity estimation errors also decrease as the number of satellites increases. To verify the robustness of LQG-VTL, we confirm that LQG-VTL can estimate position/velocity and measurements successively compared to LF-STL in temporal signal attenuation of 30 dB-Hz during 4 seconds.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.1
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• pp.128-135
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• 2009

Techniques for tracking the same region of physical space with the temporal sequences of images by matching the contours of constant phase show robust and stable performance in relative to the tracking techniques using or assuming the constant intensity. Using this property, we describe an algorithm for obtaining the robust motion parameters caused by the global camera motion. First, we obtain the optical flow based on the phase of spacially filtered sequential images on the region in a direction orthogonal to orientation of each component of gabor filter bank. And then, we apply the least squares method to the optical flow to determine the affine motion parameters. We demonstrate hat proposed method can be applied to the vision based pointing device which estimate its motion using the image including the display device which cause lighting condition varieties and noise.

• Journal of the Korean Society of Marine Environment & Safety
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• v.20 no.2
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• pp.202-209
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• 2014

In this paper, a developed device for detecting target's location and avoiding collision is proposed. Velocity and acceleration model of target are derived to estimate target's information, i.e. position, velocity and acceleration considering process and measurement noise. Kalman filtering method applied to the estimation process and its results was confirmed by simulation. The distance measurements system using laser sensor for moving target system is also developed to confirm the effectiveness of the proposed scheme. Experiments to get information of moving target with velocity and acceleration model was executed. The data with filtering and without filtering was compared by experiments. Discontinuous measured data was changed to smooth and continuous data by Kalman filtering. It is confirmed that desired data was obtained by applying proposed scheme. UI for measuring and monitoring the target data is developed and visual and auditory alarm function is attached on the system Finally, position estimation system of moving target with good performance is achieved by low price equipments.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.4
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• pp.38-46
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• 2011

This paper presents roll angle estimator which used Kalman filter. Recently, the uses of the ELSD (Electronic Limited Slip Differential) and TVD(Torque Vectoring Differential) for vehicle yaw control are studied in many researches. However the roll angle can be negative effect of ELSD and TVD control. Therefore the information of roll angle can be used for vehicle yaw control. Moreover it can be used for rollover prevent control. Recently, most of the vehicles use lateral acceleration and yaw rate sensor. In this paper, design of Kalman filter which used lateral acceleration and yaw rate information is developed. In this paper, in order to verify the estimator ability, the CarSim and Matlab/Simulink are used.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.4
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• pp.65-71
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• 2020

In order to accurately track the trajectory of the smartphone indoors and outdoors, the WiFi Fingerprint method and the Pedestrian Dead Reckoning method are fused. The former can estimate the absolute position, but an error occurs randomly from the actual position, and the latter continuously estimates the position, but there are accumulated errors as it moves. In this paper, the model and Kalman Filter equation to fuse the estimated position data of the two methods were established, and optimal system parameters were derived. According to covariance value of the system noise and measurement noise the estimation accuracy is analyzed. Using the measured data and simulation, it was confirmed that the improved performance was obtained by complementing the two methods.