• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.169.2-169.2
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• 2012

고기동 위성에 탑재된 GPS 수신기의 위성체의 기준 위치, 속도 및 시간의 정보를 제공한다. 특히 저궤도 관측위성은 빠른 동적 특성으로 인하여 GPS 위성 신호 획득 및 추적이 어려울 경우 연속적인 항행해를 제공하기 어려울 수 있다. 이를 위하여 위성 GPS 수신기는 지상용과 달리 넓은 대역폭의 신호 획득 및 추적이 가능한 RF수신단이 탑재되어 있으며 필터 기반의 궤도전파기가 탑재되어 있어 있다. 뿐만 아니라 GPS 수신기기의 상태 데이터 제공 및 고속 데이터 처리를 위하여 고성능 CPU가 탑재되어 있다. 특히 탑재된 궤도전파기는 고성능 필터 기반으로 설계되어 있으며 이를 이용하면 GPS 신호 추적이 되지 않은 상황에서도 비교적 정확하고 연속적인 항행해가 제공하게 된다. 본 논문에서는 저궤도 관측위성에 탑재된 GPS 수신기가 초기 위성운영에서 어떠한 절차에 의하여 동작이 되며 위성의 빠른 동적 특성에서 GPS 수신기의 가시성 및 추적 위성개수 분석 및 이를 바탕으로 위치 및 속도 정밀도가 어느 정도 되는지에 대한 성능 분석 결과를 정리 하였다. 본 논문 결과는 향후 고기동 위성의 GPS 수신기 및 관련 운영에 도움이 될 것으로 판단된다.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.3
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• pp.253-257
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• 2020

The local information processing devices are devices that process information by converting voltage, current, and digital electric signals from legacy-type power facility into IEC 61850 based data. It acquires and processes the operation information of legacy-type power facility, performs control of power facility, and interlock function using internal logic. In particular, the time to convert data to process input and output information for a device is important because a number of protection relay input and output signals are handled by only one device. This paper introduces test methods and cases for measuring IEC 61850 communication function and input/output data conversion time of local information processing device.

• Journal of the Institute of Convergence Signal Processing
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• v.24 no.1
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• pp.34-41
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• 2023

In recent years, as the range of human activities has increased, the introduction of alien species has become frequent. Among them, raccoons have been designated as harmful animals since 2020. Raccoons are similar in size and shape to raccoon dogs, so they generally need to be distinguished in capturing them. To solve this problem, we use VGG19, ResNet152V2, InceptionV3, InceptionResNet and NASNet, which are CNN deep learning models specialized for image classification. The parameters to be used for learning are pre-trained with a large amount of data, ImageNet. In order to classify the raccoon and raccoon dog datasets as outward features of animals, the image was converted to grayscale and brightness was normalized. Augmentation methods were applied using left and right inversion, rotation, scaling, and shift to create sufficient data for transfer learning. The FCL consists of 1 layer for the non-augmented dataset while 4 layers for the augmented dataset. Comparing the accuracy of various augmented datasets, the performance increased as more augmentation methods were applied.

• Journal of the Institute of Convergence Signal Processing
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• v.13 no.4
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• pp.166-172
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• 2012

The standard wave height measurement system is usually based on spectrum analysis for measuring wave height. The spectrum analysis is complicated because of the FFT, and the FFT is not for real time processing since it requires the saved data segments. In this paper, we carried out the performance evaluation of real-time and simpler wave height measurement system using the kalman filter and inertial sensors. The kalman filter theory is complicated, but its algorithm is simpler than the FFT and the kalman filter is used to estimate wave height by integrating acceleration data. But the accumulated error is occurred when the acceleration data is integrated. We developed the algorithm using the wind wave characteristic to decrease the accumulated error. In this paper, the performance evaluation of the wave height measurement system is carried out for various wind wave conditions. Through the experiments, we verified that it shows high measurement performance with the 3.5% margin of error in wind wave condition.

• Plant Journal
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• v.17 no.4
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• pp.53-60
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• 2021

The purpose of this study was to develop a portable vibration analyzer that is effective for acquiring and analyzing vibration data of rotating equipment of a power plant and a domestic vibration monitoring system manufacturer Nada Co., Ltd. The hardware of the developed portable vibration analyzer minimizes measurement errors by calibrating the measured values obtained through measurement uncertainty for calibration of the measuring devices in the system, and is composed of a signal processing device with high resolution through high speed data processing. The software structure implements a variety of vibration plots to execute a detailed analysis program, and applies algorithms to measure and remove noise caused by disturbances while operating a rotating machine. The developed product contributed greatly to increase the user's mobility and performance, as well as to reduce the purchase cost due to localization.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.11
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• pp.149-156
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• 2012

A digital input class-D audio amplifier is presented for digital hearing aid. The class-D audio amplifier is composed of digital and analog circuits. The analog circuit converts a digital input to a analog audio signal (DAC) with noise suppression in the audio band. An interpolated digital delta-sigma modulator is used to convert data types between digital signal processor (DSP) and digital-to-analog converter (DAC). An 16-bit, 25-kbps pulse code modulated (PCM) input is interpolated to 16-bit, 50-kbps by a digital filter. The output signal of interpolation filter is noise-shaped by a third-order digital sigma-delta modulator (SDM). As a result, 1.5-bit, 3.2-Mbps signal is applied to simple digital to analog converter.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.6
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• pp.590-596
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• 2004

Neural network-based signal classification systems are increasingly used in the analysis of large volumes of data obtained in NDE applications. Ultrasonic inspection methods on the other hand are commonly used in the nondestructive evaluation of welds to detect flaws. An important characteristic of ultrasonic inspection is the ability to identify the type of discontinuity that gives rise to a peculiar signal. Standard techniques rely on differences in individual A-scans to classify the signals. This paper proposes an ultrasonic signal classification technique based on the information tying in the neighboring signals. The approach is based on a 2-dimensional Fourier transform and the principal component analysis to generate a reduced dimensional feature vector for classification. Results of applying the technique to data obtained from the inspection of actual steel welds are presented.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.2
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• pp.58-63
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• 2002

One of the important problems of OFDM system is the large PAPR of the output signal, which can result the significant signal distortion in presence of nonlinear amplifiers. To reduce the PAPR, we use fundamentally the level clipping and propose the modified mapping/demapping method for effective reducing the PAPR of the OFDM signals with level clipping. We can significantly improve the BER performance characteristics for the OFDM system. We discussed, through extensive computer simulations, the effects of level clipping and modified mapping/demapping method on the performance of OFDM system including the trade off between bandwidth expansion and BER performance and between bandwidth efficiency and BER performance.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.12
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• pp.1122-1132
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• 2012

Compressed sensing has been applied to many fields such as images, speech signals, radars, etc. It has been mainly applied to stationary signals, and reconstruction error could grow as compression ratios are increased by decreasing measurements. To resolve the problem, speech signals are divided into frames and processed in parallel. The frames are made sparse by dictionary learning, and adaptive compressed sensing is applied which designs the compressed sensing reconstruction matrix adaptively by using the difference between the sparse coefficient vector and its reconstruction. Through the proposed method, we could see that fast and accurate reconstruction of non-stationary signals is possible with compressed sensing.

• Information and Communications Magazine
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• v.9 no.9
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• pp.72-85
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• 1992

The throughput requirement for many digital signal processing is such that multiple processing units are essential for real-time implementation. Advances in VLSI technology make it feasible to design and implement computer systems consisting of a large number of function units. The research on a very high throughput VLSI architecture for digital signal processing applications requires the development of an algorithm, decomposition scheme which can minimize data communication requirements as well as minimize computational complexity. The objectives of the research are to investigate computationally efficient algorithms for solution of the class of problems which can be modeled as DLSI systems or adaptive system, and develop VLSI architectures and associated multiprocessor systems which can be used to implement these algorithms in real-time. A new VLSI architecture for real-time 2-D digital signal processing applications is proposed in this research. This VLSI architecture extends the concept of having a single processing units in a chip. Because this VLSI architecture has the advantage that the complexity and the number of computations per input does not increase as the size of the input data in increased, it can process very large 2-D date in near real-time.