• Title/Summary/Keyword: initialization method

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A Study on Applying the Adaptive Window to Detect Objects Contour (물체의 윤곽선 검출을 위한 Adaptive Window적용에 관한 연구)

  • 양환석;서요한;강창원;박찬란;이웅기
    • Journal of the Korea Society of Computer and Information
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    • v.3 no.2
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    • pp.57-67
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    • 1998
  • In order to extract the contour of interesting object in the image, Kass suggested the Active Contour Model called "Snakes" The speed of this model is slow and this model is sensitive of initialization. In order to improve these problems, Gunn extracted the accurate contour by using two initializations, and operated to less sensitive of initialization. This method could extract more accurate contour than the existing method, but it had no effect in the speed and it was sensitive of noise. This paper applied to the Energy Minimization Algorithm about only the pixel within the window applying the window of $8{\times}8$ size at each contour point consisting Snakes in order to solve these problems. In order to less sensitive of noise which exists within image, it suggests a method that moves the window to vertical direction for the gradient of each contour point.our point.

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Calibration technique of gimballed inertial navigation system using the velocity error initialization (속도오차 초기화를 이용한 김블형 관성항법시스템의 교정기법)

  • 김천중;박정화;박흥원
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.860-863
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    • 1996
  • In this paper, we formulate the extended Kalman filter for calibration of gimballed inertial navigation system (GINS) at a pure navigation mode with 1500 ft/sec initial velocity and compare its performance to the linear Kalman filter's by using Monte-Carlo analysis method. It has been shown that estimation performance of the extended Kalman filter is better than that of the linear Kalman filter.

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Performance Comparison of CEALM and NPSOL

  • Seok, Hong-Young;Jea, Tahk-Min
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.169.4-169
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    • 2001
  • Conventional methods to solve the nonlinear programming problem range from augmented Lagrangian methods to sequential quadratic programming (SQP) methods. NPSOL, which is a SQP code, has been widely used to solve various optimization problems but is still subject to many numerical problems such as convergence to local optima, difficulties in initialization and in handling non-smooth cost functions. Recently, many evolutionary methods have been developed for constrained optimization. Among them, CEALM (Co-Evolutionary Augmented Lagrangian Method) shows excellent performance in the following aspects: global optimization capability, low sensitivity to the initial parameter guessing, and excellent constraint handling capability due to the benefit of the augmented Lagrangian function. This algorithm is ...

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A Fuzzy Clustering Method based on Genetic Algorithm

  • Jo, Jung-Bok;Do, Kyeong-Hoon;Linhu Zhao;Mitsuo Gen
    • Proceedings of the IEEK Conference
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    • 2000.07b
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    • pp.1025-1028
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    • 2000
  • In this paper, we apply to a genetic algorithm for fuzzy clustering. We propose initialization procedure and genetic operators such as selection, crossover and mutation, which are suitable for solving the problems. To illustrate the effectiveness of the proposed algorithm, we solve the manufacturing cell formation problem and present computational comparisons to generalized Fuzzy c-Means algorithm.

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Adaptive Control of CNC Boring Machine by Application of the Variance Perturbation Method (분산 섭동법 에 의한 CNC보오링 머시인 의 적응제어)

  • 이종원
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.8 no.1
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    • pp.65-70
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    • 1984
  • A recursive parameter estimation method is applied to spindle deflection model during boring process. The spindle infeed rate is then determined to preserve the diametral tolerance of bore. This estimation method is further extended to adaptive control by application of the variance perturbation method. The results of computer simulation attest that the proposed method renders the optimal cutting conditions, maintaining the diametral accuracy of bore, regardless of parameter fluctuations. The proposed method necessitating only post-process measurements features that initialization of parameter guess values in simple, a priori knowledge on parameter variations is not needed and the accurate estimation of optimal spindle infeed rate is obtained, even if the parameter estimation may be poor.

Multi-Sensor Multi-Target Passive Locating and Tracking

  • Liu, Mei;Xu, Nuo;Li, Haihao
    • International Journal of Control, Automation, and Systems
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    • v.5 no.2
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    • pp.200-207
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    • 2007
  • The passive direction finding cross localization method is widely adopted in passive tracking, therefore there will exist masses of false intersection points. Eliminating these false intersection points correctly and quickly is a key technique in passive localization. A new method is proposed for passive locating and tracking multi-jammer target in this paper. It not only solves the difficulty of determining the number of targets when masses of false intersection points existing, but also solves the initialization problem of elastic network. Thus this method solves the problem of multi-jammer target correlation and the elimination of static false intersection points. The method which dynamically establishes multiple hypothesis trajectory trees solves the problem of eliminating the remaining false intersection points. Simulation results show that computational burden of the method is lower, the elastic network can more quickly find all or most of the targets and have a more probability of locking the real targets. This method can eliminate more false intersection points.

Continuous Digit Recognition Using the Weight Initialization and LR Parser

  • Choi, Ki-Hoon;Lee, Seong-Kwon;Kim, Soon-Hyob
    • The Journal of the Acoustical Society of Korea
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    • v.15 no.2E
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    • pp.14-23
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    • 1996
  • This paper is a on the neural network to recognize the phonemes, the weight initialization to reduce learning speed, and LR parser for continuous speech recognition. The neural network spots the phonemes in continuous speech and LR parser parses the output of neural network. The whole phonemes recognized in neural network are divided into several groups which are grouped by the similarity of phonemes, and then each group consists of neural network. Each group of neural network to recognize the phonemes consisits of that recognize the phonemes of their own group and VGNN(Verify Group Neural Network) which judges whether the inputs are their own group or not. The weights of neural network are not initialized with random values but initialized from learning data to reduce learning speed. The LR parsing method applied to this paper is not a method which traces a unique path, but one which traces several possible paths because the output of neural network is not accurate. The parser processes the continuous speech frame by frame as accumulating the output of neural network through several possible paths. If this accumulated path-value drops below the threshold value, this path is deleted in possible parsing paths. This paper applies the continuous speech recognition system to the threshold value, this path is deleted in possible parsing paths. This paper applies the continuous speech recognition system to the continuous Korea digits recognition. The recognition rate of isolated digits is 97% in speaker dependent, and 75% in speaker dependent. The recognition rate of continuous digits is 74% in spaker dependent.

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Development and Assessment of Dynamical Seasonal Forecast System Using the Cryospheric Variables (빙권요소를 활용한 겨울철 역학 계절예측 시스템의 개발 및 검증)

  • Shim, Taehyoun;Jeong, Jee-Hoon;Ok, Jung;Jeong, Hyun-Sook;Kim, Baek-Min
    • Atmosphere
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    • v.25 no.1
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    • pp.155-167
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    • 2015
  • A dynamical seasonal prediction system for boreal winter utilizing cryospheric information was developed. Using the Community Atmospheric Model, version3, (CAM3) as a modeling system, newly developed snow depth initialization method and sea ice concentration treatment were implemented to the seasonal prediction system. Daily snow depth analysis field was scaled in order to prevent climate drift problem before initializing model's snow fields and distributed to the model snow-depth layers. To maximize predictability gain from land surface, we applied one-month-long training procedure to the prediction system, which adjusts soil moisture and soil temperature to the imposed snow depth. The sea ice concentration over the Arctic region for prediction period was prescribed with an anomaly-persistent method that considers seasonality of sea ice. Ensemble hindcast experiments starting at 1st of November for the period 1999~2000 were performed and the predictability gain from the imposed cryospheric informations were tested. Large potential predictability gain from the snow information was obtained over large part of high-latitude and of mid-latitude land as a result of strengthened land-atmosphere interaction in the modeling system. Large-scale atmospheric circulation responses associated with the sea ice concentration anomalies were main contributor to the predictability gain.

Analysis of Coast Topography by RTK GPS and Echo Sounder

  • Lee, Jea-One;Kim, Jin-Soo
    • Korean Journal of Geomatics
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    • v.2 no.1
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    • pp.57-64
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    • 2002
  • Measuring the depth of water is very important in ensuring the protection and safety of seaside. There are many difficulties in making the contour bathymetric map, and contour line due to the limitation of continuous measurement of water depth and collimation with the conventional measuring and positioning methods. But the real-time kinematic GPS (RTK GPS) positioning using a carrier phase enables us to decide a precise position without breaking a signal even under the condition of a moving environment. It is also possible to obtain an accurate depth of water in real time with a fathometer through the measuring of time delay between sending and receiving epochs. This research aims at investigation of accuracy potential of RTK GPS in combination with Echo Sounder(E/S) for the coastal mapping. Apart from this purpose, the accuracy of ambiguity resolution with the OTF(On the Fly) method was tested with respect to the initialization time. The result shows that the accuracy is better than 1cm with 5-minute initialization in the distance of 10km baseline. The seaside topography was measured by the RTK GPS only, on the other hand the seafloor topography was surveyed in combination of RTK GPS and E/S. Comparing to the volume of seaside measured by RTK GPS and digital topographical map, the difference of only 2 % was achieved. This indicates that the coastal mapping with RTK GPS is successfully conducted. In addition it is also demonstrated that the 3-dimensional perspective model resulted from the undersea topography measured by RTK GPS and E/S is very close to that from the digital map. Through this study, it was verified that RTK GPS is to be very useful method in the analysis of coastal morphology owing to its capability of getting the precise DTM for the using of harbor reclamation, dredging, and the estimation of soil movement in a river.

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Sensitivity Study of Smoothed Particle Hydrodynamics

  • Kim, Yoo-Il;Nam, Bo-Woo;Kim, Yong-Hwan
    • Journal of Ship and Ocean Technology
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    • v.11 no.4
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    • pp.29-54
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    • 2007
  • Systematic sensitivity analysis of smoothed particle hydrodynamics method (SPH), a gridless Lagrangian particle method, was carried out in this study. Unlike traditional grid-based numerical schemes, systematic sensitivity study for computational parameters is very limited for SPH. In this study, the effect of computational parameters in SPH simulation is explored through two-dimensional dam-breaking and sloshing problem. The parameters to be considered are the speed of sound, the type of kernel function, the frequency of density re-initialization, particle number, smoothing length and pressure extraction method. Through a series of numerical test, detailed information was obtained about how SPH solution can be more stabilized and improved by adjusting computational parameters.