• Journal of the Institute of Electronics and Information Engineers
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• v.53 no.5
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• pp.47-54
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• 2016

In the underwater environment, high resolution can be achieved in the range direction by transmitting and receiving a signal of a particular band and/or waveform. The design of a transmit signal used in the active sonar is very important in order to detect a cylindrical object within a short distance less than 1 km, which is the detection distance of this paper. Designing a transmit signal optimal to a sonar requires appropriate selection of its center frequency and bandwidth, which allows the maximum detection distance of a sonar. In this paper, in terms of maximizing echo excess and signal to noise ratio (SNR), optimum frequency analysis is carried out under various conditions of diverse parameters. In addition, the investigation focused on the determinating a bandwidth is also performed for the purpose of satisfying the performance requirement of range resolution and azimuth resolution.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.13 no.1
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• pp.60-68
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• 1999

This paper deals with the tracking control problem of industrial robotic manipulators with unknown or changing dynamics. The proposed method makes use of multiple moodels and switching mechanism by fuzzy inference of the manipulator in an indirect adaptive controller architecture. The models used for the indmtification of the manipliator are identical, except for the initial estimates of the unknown inertial pararmeters of the manipulator and its load. The torque input that is applied to the joint actuators is determined at every instant by the identification model that best approximates the robot dynamics. Simulation results are also included to dermnstrate the improvement in the tracking perfermance when the proposed method is used.s used.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.1
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• pp.8-14
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• 2002

In this paper, we realized a real-time text-independent speaker recognition system using gaussian mixture model, and applied frame level likelihood normalization method which shows its effects in verification system. The system has three parts as front-end, training, recognition. In front-end part, cepstral mean normalization and silence removal method were applied to consider speaker's speaking variations. In training, gaussian mixture model was used for speaker's acoustic feature modeling, and maximum likelihood estimation was used for GMM parameter optimization. In recognition, likelihood score was calculated with speaker models and test data at frame level. As test sentences, we used text-independent sentences. ETRI 445 and KLE 452 database were used for training and test, and cepstrum coefficient and regressive coefficient were used as feature parameters. The experiment results show that the frame-level likelihood method's recognition result is higher than conventional method's, independently the number of registered speakers.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.3
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• pp.385-396
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• 1993

In this paper, a improved method of digital image analysis required in basic medical science for diagnosis of cells was proposed. The object image was the thyroid gland cell image, and the purpose was automatic discrimination of three classes cells(normal cell, follicular neoplastic cells, and papillary neoplastic cells) by difference of chromatin patterns. To segment the cell nucleus from background, the region segmentation algorithm by edge tracing was proposed. And feature parameter was obtained from discrete Fourier transformation of image. After construct a feature sample group of each cells, experiment of discrimination was executed with any verification cells. As a consequency of using features proposed in this paper, get a better recognition rate(70-90%) than previously reported papers, and this method give shape to get objectivity and fixed quantity in diagnosis of cells, The methods described in this paper be used immediately for discrimination of neoplastic cells.

• Aerospace Engineering and Technology
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• v.2 no.1
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• pp.22-28
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• 2003

This paper presents a method for estimating static aerodynamic derivatives by analyzing data obtained from the flying quality evaluation test of a small canard aircraft. The aerodynamic derivatives extracted from maximum likelihood estimation method and from the proposed method in this paper are compared in the same polt. Reliable static aerodynamic derivatives were extracted from a limited number of the flight tests by the proposed method. The parameter data obtained from this method can be used as reference for the conventional parameter identification methods such as maximum likelihood estimation method.

• Journal of the Korean Society of Propulsion Engineers
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• v.15 no.2
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• pp.1-7
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• 2011

The UAV(Unmanned Aerial Vehicle) which is remotely operating with long endurance in high altitude must have a very reliable propulsion system. The precise fault diagnostic system of the turboprop engine as a propulsion system of this type UAV can promote reliability and availability. This work proposes a diagnostic method which can identify the faulted components from engine measuring parameter changes using Fuzzy Logic and quantify its faults from the identified fault pattern using Neural Network Algorithms. It is found by evaluation examples that the proposed diagnostic method can detect well not only single type faults but also multiple type faults.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2010.11a
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• pp.499-505
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• 2010

The UAV(Unmanned Aerial Vehicle) which is remotely operating with long endurance in high altitude must have a very reliable propulsion system. The precise fault diagnostic system of the turboprop engine as a propulsion system of this type UAV can promote reliability and availability. This work proposes a diagnostic method which can identify the faulted components from engine measuring parameter changes using Fuzzy Logic and quantify its faults from the identified fault pattern using Neural Network Algorithms. It is found by evaluation examples that the proposed diagnostic method can detect well not only single type faults but also multiple type faults.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2010.05a
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• pp.279-287
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• 2010

This paper surveys the recent research activities regarding dynamical modeling of high amplitude - high frequency thermo-acoustic instabilities occurring in gas-turbine engines, rockets, and etc, which are fundamental to actively control of such phenomena. For this, we introduces the reduced-order system modeling approaches, conducted after 1990s. Particularly, we deal with the grey-box approach, which determines the structure of the model based on physical rules and uses system's input-output data for estimating parameters of the model, and the black-box approach, which uses model structure without physics-based interpretation. At the end of the paper, we briefly discuss future directions and feasibilities of the research in this field.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.37 no.6
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• pp.556-561
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• 2009

The UAV(Unmanned Aerial Vehicle) that is remotely operating in various and long flight environments must have a very reliable propulsion system. Precise fault diagnosis of the turbo shaft engine for the Smart UAV that has the vertical take-off, landing and forward flight behaviors can promote reliability and availability. This work proposes a new diagnostic method that can identify the faulted components from engine measuring parameter changes using Fuzzy Logic and quantify its faults from the identified fault pattern using Neural Network Algorithms. The proposed diagnostic method can detect not only single fault but also multiple faults.

• The Journal of the Acoustical Society of Korea
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• v.33 no.1
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• pp.68-74
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• 2014

In a previous work, we proposed a novel approach of histogram equalization using a supplement set which is composed of centroids of Fuzzy C-Means of the background utterances. The performance of the proposed method is affected by the size of the supplement set, but it is difficult to find the best size at the point of recognition. In this paper, we propose a histogram equalization using a supplement set for majority voting based speaker identification. The proposed method identifies test utterances using a majority voting on the histogram equalization methods with various sizes of supplement sets. The proposed method is compared with the conventional feature normalization methods such as CMN(Cepstral Mean Normalization), MVN(Mean and Variance Normalization), and HEQ(Histogram Equalization) and the histogram equalization method using a supplement set.