• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.2
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• pp.95-101
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• 2005

In this paper, we proposed a learning algorithm for the neuro-fuzzy modeling using a learning rule to adapt clustering. The proposed algorithm includes the data partition, assigning the rule into the process of partition, and optimizing the parameters using predetermined threshold value in self-constructing algorithm. In order to improve the clustering, the learning method of neuro-fuzzy model is extended and the learning scheme has been modified such that the learning of overall model is extended based on the error-derivative learning. The effect of the proposed method is presented using simulation compare with previous ones.

• Transactions of the Korean Society of Automotive Engineers
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• v.1 no.3
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• pp.55-62
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• 1993

Autoregressive moving average(ARMA) model which is a time domain parametric modeling method is implemented for modeling and reproducing characteristics of exhaust noise of an automobile in various RPM range. Experiments have been carried out using 9 set of exhaust noise signals measured at 1,000-3,000 RPM range. Characteristics of sampled signals were estimated using ARMA modeling and Akaike's FPE(final prediction error) criterion to define exact model structure and for model validation. The digital filter consisted of the esitmated ARMA(70,1) model parameters was programed to reproduce exhaust noise. The spectral analysis of reproduced noise is very close to original. The results show that our approaching technique for reproducing acoustic characteristics is valid and feasible to apply in the field of noise quality control.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.33 no.2
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• pp.75-83
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• 2005

NASA/DLR Gravity Recovery and Climate Experiment (GRACE) mission, which consists of two co-orbiting low altitude satellites, is to measure the Earth gravity field with unprecedented accuracy. Its key instruments include inter-satellite ranging systems and three-axis accelerometers. For the preliminary design and requirements analysis, extensive instrument simulation models are developed. These modeling techniques and orbit-gravity field estimation techniques are described.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1994.06a
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• pp.25-36
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• 1994

The sheet metal forming process is one of the most important manufacturing processes in the modern industry. From the view point of mechanics involved, it is very difficult to predict whether a newly designed sheet metal part can be formed without defects such as fracture, wrinkling and surface unevenness, etc. In order to reduce the effort taken in the trial-and-error process and to control the process effectively, a systematic method for process modeling is to required. The aim of sheet forming simulation through the process modeling is to reduce the lead time for die disign and manufacture by process modeling is to reduce the lead time for die design and manufacture by means of investigating the deformation mechanics and the mutual interaction between the process parameters. In this paper, the necessity, the present status, and the future technology about CAE of sheet forming simulation have been discussed.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.521-522
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• 2006

This paper presents behavioral models using SIMULINK and Verilog-a for a PLL based fractional-N frequency synthesizer. The SIMULINK modeling was built in the frequency-time mixed domain whereas the Verilog-a modeling was built purely in the time domain. The simulated results of the two models were verified to show the same performance within the error tolerance. This top-down design method can provide the readiness for the transistor-level design.

• ETRI Journal
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• v.33 no.6
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• pp.914-923
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• 2011

This paper concerns robust and reliable speaker model training for text-independent speaker verification. The baseline speaker modeling approach is the Gaussian mixture model (GMM). In text-independent speaker verification, the amount of speech data may be different for speakers. However, we still wish the modeling approach to perform equally well for all speakers. Besides, the modeling technique must be least vulnerable against unseen data. A traditional approach for GMM training is expectation maximization (EM) method, which is known for its overfitting problem and its weakness in handling insufficient training data. To tackle these problems, variational approximation is proposed. Variational approaches are known to be robust against overtraining and data insufficiency. We evaluated the proposed approach on two different databases, namely KING and TFarsdat. The experiments show that the proposed approach improves the performance on TFarsdat and KING databases by 0.56% and 4.81%, respectively. Also, the experiments show that the variationally optimized GMM is more robust against noise and the verification error rate in noisy environments for TFarsdat dataset decreases by 1.52%.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.8
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• pp.482-491
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• 2003

In this paper are presented kinematic and dynamic modeling and path-tracking of four-wheeled mobile robots with 2 d.o.f haying the limited drive-torques. Controllability of wheeled-mobile robots is revealed by the kinematic model. Instantaneously coincident coordinate system, force/torque propagation and Newton's equilibrium law are used to drive the dynamic model. When drive-torques generated by inverse dynamics exceed the limitation, we make wheeled-mobile robots follow the reference path by modifying the planned reference trajectory with time-scaling. The controller is introduced to compensate for error owing to modeling uncertainty and measurement noise. And simulation results prove that method proposed by this paper is efficient.

• Journal of Korean Institute of Industrial Engineers
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• v.37 no.3
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• pp.264-270
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• 2011

A new method for creating a logical data model is proposed. The logical data model developed by the method defines table, primary key, foreign key, and fields. The framework of the logical data model is constructed by modeling the relationships between events and their related entity types. The proposed method consists of a series of objective and quantitative decisions such as maximum cardinality of relationships and functional dependency between the primary key and attributes. Even beginners to database design can use the methology as long as they understand such basic concepts about relational databases as primary key, foreign key, relationship cardinality, parent-child relationship, and functional dependency. The simple and systematic approach minimizes decision errors made by a database designer. In practial database design the method creates a logical data model in Boyce-Codd normal form unless the user of the method makes a critical decision error, which is very unlikely.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.51 no.1
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• pp.45-51
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• 2002

In this paper are presented dynamic modeling and path-tracking of differential drive wheeled-mobile robots(WMRs) having the limited drive-torques. Instantaneously coincident coordinate system, force/torque propagation and Newton's equilibrium law are used to induce the dynamic model. When drive-torques generated by inverse dynamics exceed the limitation, we make wheeled-mobile robots follow the reference path by modifying the planned reference trajectory with time-scaling method. The controller is introduced to compensate for error owing to modeling uncertainty and measurement noise. And simulation results prove that method proposed by this paper is efficient.

• Korean Journal of Geomatics
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• v.2 no.1
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• pp.31-35
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• 2002

This paper describes an experiment for three-dimensional positioning for a pair of KOMPSAT stereostrips using the ancillary data and a single ground control point. The photogrammetric model for three-dimensional positioning was performed as follows: first, initialization of orbital and attitude parameters derived from ancillary data; second, adjustment of orbital and attitude parameters for the satellite to minimize the ground position error with respect to a GCP using the collinearity condition; third, determination of actual satellite position; and lastly, space intersection. This model was tested for a pair of stereo strips with 0.6 base-to-height ratio and GCPs identified from a 1:5,000 scale digital map. As the result, the satellite position of offset was corrected by only one GCP and the accuracy for the geometric modeling showed 38.89m RMSE.