• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.1321-1325
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• 1993

This paper investigates the use of Fuzzy vector quantizer(FVQ) in speech synthesis. To compress speech data, we employ K-means algorithm to design codebook and then FVQ technique is used to analysize input speech vectors based on the codebook in an analysis part. In FVQ synthesis part, analysis data vectors generated in FVQ analysis is used to synthesize the speech. We have fined that synthesized speech quality depends on Fuzziness values in FVQ, and the optimum fuzziness values maximized synthesized speech SQNR are related with variance values of input speech vectors. This approach is tested on a sentence, and we compare synthesized speech by a convensional VQ with synthesized speech by a FVQ with optimum Fuzziness values.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.11
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• pp.2655-2663
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• 1993

In order to evaluate the relative significance of tolerance management of various elements in a VHS VTR tape transport system, the effect of geometric variations of the elements from standard design values on the tape traveling path is studied. The tape is modeled as a string and each element in the tape transport system is modeled as a cylinder whose radius, position vector and orientation vector are specified. An numerical algorithm is proposed to find the coordinates of tape entry points and tape exit points for the elements from which the tape traveling path can be completely described. By using the suggested algorithm, an error sensitivity analysis of tape traveling path due to the geometric variations of tape transport elements is performed for a particular model in the market and the elements demanding relatively strict tolerance management are identified.

• Journal of Electrical Engineering and Technology
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• v.9 no.2
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• pp.726-732
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• 2014

A current flowing through a distribution conductor produces induced voltage, which is harmful to a telecommunication line. Previous research on induced voltage has been focused on single-circuit lines in the distribution system. However, the double-circuit lines, referred to as parallel distribution lines, are widely used in distribution systems because they have significant economic and environmental advantages over single-circuit lines. Therefore, a study on the induced voltage in double-circuit lines is needed. This paper presents a method of calculating the induced voltage in a parallel distribution system using four-terminal parameters and vector analysis. The calculation method is verified by the Electromagnetic Transient Program (EMTP) simulation.

• Proceedings of the KIEE Conference
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• 1995.07a
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• pp.56-58
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• 1995

Dynamic characteristics of the vector controlled induction motor has been analysed using d-q equivalent circuit. However, for the design of the induction motor, the analysis of an accurate response characteristic are needed. In this paper, dynamic characteristic analysis method using 2-D Finite Element Method (FEM), which takes the motion equation of the rotor into account and considers the physical motion of the rotor by an automatic subdivision of mesh, are explained.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1086-1088
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• 2005

It is necessary to modify the state-of-the-art of vector control theory, because of the phase asymmetry(static end effect) in the Linear Induction Motor(LIM). The dynamic characteristic analysis method of the vector controlled LIM using coupled FEM and control algorithm taking into account the movement is proposed. The focus of this paper is the analysis relative to phenomena of static end effect due to the motor structure. To prove the propriety of the proposed method, the Digital Signal Processor(DSP) installed experimental devices are equipped and the experiment is performed.

• Design & Manufacturing
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• v.17 no.1
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• pp.27-32
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• 2023

In this paper, we intend to predict the mass of the spiral using CAE and machine learning. First, We generated 125 data for the experiment through a complete factor design of 3 factors and 5 levels. Next, the data were derived by performing a molding analysis through CAE, and the machine learning process was performed using a machine learning tool. To select the optimal model among the models learned using the learning data, accuracy was evaluated using RMSE. The evaluation results confirmed that the Support Vector Machine had a good predictive performance. To evaluate the predictive performance of the predictive model, We randomly generated 10 non-overlapping data within the existing injection molding condition level. We compared the CAE and support vector machine results by applying random data. As a result, good performance was confirmed with a MAPE value of 0.48%.

• The Mathematical Education
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• v.19 no.1
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• pp.57-58
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• 1980

• Proceedings of the Korean Society of Plant Pathology Conference
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• 2005.10a
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• pp.67-69
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• 2005

• Journal of The Korean Astronomical Society
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• v.29 no.spc1
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• pp.307-308
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• 1996

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.13 no.1
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• pp.12-18
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• 2013

Motor imagery classification in electroencephalography (EEG)-based brain-computer interface (BCI) systems is an important research area. To simplify the complexity of the classification, selected power bands and electrode channels have been widely used to extract and select features from raw EEG signals, but there is still a loss in classification accuracy in the state-of- the-art approaches. To solve this problem, we propose a discriminative feature extraction algorithm based on power bands with principle component analysis (PCA). First, the raw EEG signals from the motor cortex area were filtered using a bandpass filter with ${\mu}$ and ${\beta}$ bands. This research considered the power bands within a 0.4 second epoch to select the optimal feature space region. Next, the total feature dimensions were reduced by PCA and transformed into a final feature vector set. The selected features were classified by applying a support vector machine (SVM). The proposed method was compared with a state-of-art power band feature and shown to improve classification accuracy.