• Proceedings of the KIEE Conference
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• 1999.07e
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• pp.2431-2433
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• 1999

Phase errors of arrayed waveguide degrade the performance of AWG router, especially for dense WDM system. So it is necessary to measure the phase error and to compensate. The analysis method of the interference signal from the low coherence interferometer to measure the path length difference phase error is studied. The interference signal generated assuming the intentional path length difference errors of 0.1$\sim$0.4${\mu}m$ are analyzed and the results show that the path length difference phase error of ${\Delta}L$ within ${\pm}14^{\circ}$ of sampling phase error can be accurately measured.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.14-17
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• 2003

웨이블릿 변환 영역에서 잡음제거 방법 중 Visushrink 추정에 사용되는 경계값은 측정 데이터 수와 잡음편차에 비례하는 것으로 알려져 있으나 잡음편차가 알려지지 않은 경우 Donoho는 웨이블릿 변환 영역의 최고대역에서 잡음편차 추정 방법을 제시하였다. 본 논문에서는 분산이 데이터 수에 반비례함을 이용하여 threshold 기법을 이용하여 잡음제거 시 계산량을 감소를 목적으로 차 신호를 이용하여 측정데이터 수를 줄인 후 영상신호의 가우시안 잡음을 soft threshold 기법을 적용하고 이 기법의 실용성을 밝혔다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2008.11a
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• pp.181-184
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• 2008

The paper describes a Layered Modulation using the SVC signals and studies the properties of the modulation with respect to several parameters by the computer simulation. The SVC signals will include a base layer signal and an enhancement signal, and the base layer signal is the more important one in its channel robustness. The parameters will include a carrier frequency, a bandwidth, power level, modulation type and code rate. We analyze the demodulating and decoding process of the Layered Modulation system through several scatter plots. And then we discuss the affect of the layer signal power difference to the BER performance, which also proves the base layer signal is more important than the enhancement layer signal.

• Journal of Positioning, Navigation, and Timing
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• v.11 no.2
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• pp.127-134
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• 2022

In this paper, a low-cost, flexible GPS simulator based on USRP is designed as a general-purpose software wireless front-end. The simulator consists of a software GPS signal generator and a USRP-based RF transmitter. The simulator supports various scenarios including specified reception time, quantization bit level, I/Q data types, IF frequency, sampling frequency, SNR, ionospheric delay and user dynamics. The generated GPS RF signal is verified using the spectrum analyzer and off-the-shelf GNSS receivers such as U-blox M8T. The experimental results shows that the difference between generated and real live signal is ignorable. It is expected that designed GPS simulator can be used to GNSS signal design, receiver design and signal processing algorithms such as anti-jamming.

• ETRI Journal
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• v.45 no.2
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• pp.277-290
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• 2023

This paper proposes a method that can reduce the complexity of a system matrix by analyzing the characteristics of a pseudoinverse matrix to receive a binomial frequency division multiplexing (BFDM) signal and decode it using the least squares (LS) method. The system matrix of BFDM can be expressed as a band matrix, and as this matrix contains many zeros, its amount of calculation when generating a transmission signal is quite small. The LS solution can be obtained by multiplying the received signal by the pseudoinverse matrix of the system matrix. The singular value decomposition of the system matrix indicates that the pseudoinverse matrix is a band matrix. The signal-to-interference ratio is obtained from their eigenvalues. Meanwhile, entries that do not contribute to signal generation are erased to enhance calculation efficiency. We decode the received signal using the pseudoinverse matrix and the removed pseudoinverse matrix to obtain the bit error rate performance and to analyze the difference.

• Transactions of the Korean Society of Mechanical Engineers
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• v.18 no.4
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• pp.1057-1063
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• 1994

An instantaneous frequency analysis is a technique to examine a signature for the rotating machinery if the signal has several transitions within a cycle. This paper discusses the conditions of existing negative frequency components in the instantaneous frequency. By using a signal consisted of two frequency components, the instantaneous frequency analysis is conducted while the amplitude ratio between two frequency components has been changed. The analysis shows that, depending on the amplitude ratio, the instantaneous frequencies have averaged, zero-valued, or negative components. It turns out that the negative-valued instantaneous frequencies, which have been regarded as the noise effect, are the consequence of the calculation process for the multisignal components. The criteria of existing the negative values in instantaneous frequencies is given in terms of the relative amplitude ratio and the frequency difference. Especially when the amplitude ratio approaches to 1, the instantaneous frequency fluctuates ${\pm}\infty$ in theory, which implies that instantaneous frequency has unstable region around the amplitude ratio, 1.Also, as the frequency difference between major signal components is increased, the region of existing negative instantaneous becomes broader. In an instantaneous frequency analysis, therefore, a narrow band analysis is suggested, with extreme care if the amplitude ratio approaches to 1. In this paper, a vibration signal monitored from a rotating machinery is also examined as an application example in order to show the existence of negative instantaneous frequencies components.

• The Journal of the Acoustical Society of Korea
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• v.23 no.7
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• pp.514-520
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• 2004

There are many techniques for underwater source localization. These are the methods based on TDOA (Time Difference Of Arrival) estimation. beamforming techniques and high resolution techniques, etc. In this Paper we estimate the underwater source position using MCPSP (Modified Cross Power Spectrum Phase) function that is calculated on frequency domain using sensors of small number. However, the performances of the localizing method based on MCPSP function drops greatly in the case of CW (Continuous Wave) signal . In this Paper we proposed the TDOA estimation method for pulsed CW signal. In the Proposed method we composed of new segment including a edge of ping. This segment was computed by short-time energy detection. With theoretical representation the performances of the proposed method were analyzed under various environment.

• Design & Manufacturing
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• v.14 no.3
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• pp.8-16
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• 2020

In this study, the vibration signal of the mold was measured and analyzed to monitoring the process time and characteristics during injection molding. A 5 inch light guide plate mold was used to injection molding and the vibration signal was measured by MPU6050 acceleration sensor module attached the surface of fixed mold base. Conditions except for injection speed and packing pressure were set to the same value and the change of the vibration signal of the mold according to injection speed and packing pressure was analyzed. As a result, the vibration signal had a large change at three points: "Injection start", "V/P switchover", and "Packing end". The time difference between "injection start" and "V/P switchover" means the injection time in the injection molding process, and the time difference between "V/P switchover" and "Packing end" means the packing time. When the injection time and packing time obtained from the vibration signal of the mold are compared with the time recorded in the injection molding machine, the error of the injection time was 2.19±0.69% and the error of the packing time was 1.39±0.83%, which was the same level as the actual value. Additionally, the amplitude at the time of "injection start" increased as the injection speed increased. In "V/P switchover", the amplitude tended to be proportional to the pressure difference between the maximum injection pressure and the packing pressure and the amplitude at the "packing end" tended to the pressure difference between the packing pressure and the back pressure. Therefore, based on the result of this study, the injection time and packing time of each cycle can be monitored by measuring the vibration signal of the mold. Also, it was confirmed that the level and trend of process variables such as the injection speed, maximum injection pressure, and packing pressure can be evaluated as the change of the mold vibration during injection molding.

• Journal of Satellite, Information and Communications
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• v.12 no.1
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• pp.28-33
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• 2017

In this paper, new signal model for bio-signal detection, i.e heart beat and respiration, using CW radar. Most research on this similar topic are based on the conventional signal model which is not correct in envisaging reflected signal from the human body. The system developed based on this conventional model can not predict exact performance of the system. So in this paper modified signal model for bio-radar is proposed and then simulation for detecting heartbeat and respiration signal in AWGN, multipath environment. The detection performance difference between two signal models are discussed.the modified

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.982-986
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• 1997

A method using cutting force signal and neural network for detection tool damage is proposed. Cutting force signal is gained by tool dynamometer and the signal is prepocessed to normalize. Cutting force signal is changed by tool state. When tool damage is occurred, cutting force signal goes up in comparison with that in normal state. However,the signal goes down in case of catastrophic fracture. These features are memorized in neural network through nomalizing couse. A new nomalizing method is introduced in this paper. Fist, cutting forces are sumed up except data smaller than threshold value, which is the cutting force during non-cutting action. After then, the average value is found by dividing by the number of data. With backpropagation training process, the neural network memorizes the feature difference of cutting force signal between with and without tool damage. As a result, the cutting force can be used in monitoring the condition of cutting tool and neural network can be used to classify the cutting force signal with and without tool damage.