• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.39-45
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• 2018

Compressive sensing allows recovering an original signal which has a small dimension of the signal compared to the dimension of the entire signal in a short period of time through a small number of observations. In this paper, we proposed a method for detecting tonal signal which caused by the machinery component of a vessel such as an engine, gearbox, and support elements. The tonal signal can be modeled as the sparse signal in the frequency domain when it compares to whole spectrum range. Thus, the target tonal signal can be estimated by S-OMP (Simultaneous-Orthogonal Matching Pursuit) which is one of the sparse signal recovery algorithms. In simulation section, we showed that S-OMP algorithm estimated more precise frequencies than the conventional FFT (Fast Fourier Transform) thresholding algorithm in low SNR (Signal to Noise Ratio) region.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.12C
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• pp.1142-1148
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• 2007

In this paper, we propose ASLM (Adaptive Selective Mapping; ASLM) scheme based on peak observation for PAPR (Peak-to-Average Power Ratio) reduction of OFDM (Orthogonal Frequency Division Multiplexing) signals. The proposed scheme is composed of three steps: peak scaling, sequence selection, and SLM procedures. In the first step, the peak signal samples in the IFFT (Inverse Fast Fourier Transform) outputs of the original input sequence are scaled down. In the second step, the sub-carrier positions where the power difference between the original input sequence and the FFT output of the scaled signal is large, are identified. Then, the phase sequences having the maximum number of phase-reversed sequence words only for these positions are selected. Finally, the generic SLM procedure is performed by using only the selected phase sequences for the original input sequence. Simulation results show that the proposed scheme significantly reduces the complexity in terms of IFFT and PAPR calculation than the conventional SLM, while maintaining the PAPR reduction performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.2
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• pp.495-513
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• 2020

The correlation identification of the subsurface is a novel electrical prospecting method which could suppress stochastic noise. This method is increasingly being utilized by geophysicists. It achieves the frequency response of the underground media through division of the cross spectrum of the input & output signal and the auto spectrum of the input signal. This is subject to the spectral leakage when the cross spectrum and the auto spectrum are computed from cross correlation and autocorrelation function by Discrete Fourier Transformation (DFT, "To obtain an accurate frequency response of the earth system, we propose an improved correlation identification method which uses all phase Fast Fourier Transform (APFFT) to acquire the cross spectrum and the auto spectrum. Simulation and engineering application results show that compared to existing correlation identification algorithm the new approach demonstrates more precise frequency response, especially the phase response of the system under identification.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.1
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• pp.33-37
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• 2011

This paper presents the frequency spectral analysis based on FFT of the infrared ray fire thermal image, it is an object to deduce the conditions for determining fire alarm through the image processing with the frequency domain. After the candidate regions are separated by using pre-defined brightness value, the fast fourier transform is performed for consecutive infrared thermal images, the frequency spectral analysis of the thermal image analyzed DC and AC frequency distribution. The fire criterion of the thermal image was presented based on the analyzed result and a practicality was confirmed through the computer simulation.

• Korean Journal of Optics and Photonics
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• v.19 no.1
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• pp.1-8
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• 2008

Shack-Hartmann sensors are widely employed as a wavefront measuring device in various applications. Adaptive optics is one of the major applications. Since an adaptive optics system should be operated in real-time, high-speed wavefront sensing is essential. In high-speed operation, integration time of an image detector is very short. In this case, noises such as readout noise and photon noise greatly influence the accuracy of wavefront sensing. Therefore a fast and noise-insensitive centroid finding algorithm is required for the real-time wavefront sensing. In this paper, the multi-resolution correlation method is proposed. By employing multi-resolution images, this method greatly reduces the computation time when compared to the fast Fourier transform (FFT) correlation method. The verification is performed through the computational simulation. In this paper, the center of mass method, correlation method and multi-resolution correlation method are employed to compare the measurement accuracy of the centroid finding algorithms. The accuracy of a Shack-Hartmann wavefront sensor using the proposed algorithm is proved to be comparable to that of the conventional correlation method.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.1
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• pp.1-8
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• 2018

This paper proposes a low complexity super resolution algorithm for frequency modulated continuous wave (FMCW) radar systems for foreign object debris (FOD) detection. FOD radar has a requirement to detect foreign object in small units in a large area. However, The fast Fourier transform (FFT) method, which is most widely used in FMCW radar, has a disadvantage in that it can not distinguish between adjacent targets. Super resolution algorithms have a significantly higher resolution compared with the detection algorithm based on FFT. However, in the case of the large number of samples, the computational complexity of the super resolution algorithms is drastically high and thus super resolution algorithms are difficult to apply to real time systems. In order to overcome this disadvantage of super resolution algorithm, first, the proposed algorithm coarsely obtains the frequency of the beat signal by employing FFT. Instead of using all the samples of the beat signal, the number of samples is adjusted according to the frequency of the beat signal. By doing so, the proposed algorithm significantly reduces the computational complexity of multiple signal classifier (MUSIC) algorithm. Simulation results show that the proposed method achieves accurate location even though it has considerably lower complexity than the conventional super resolution algorithms.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.1
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• pp.39-45
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• 2009

OFDM is used for achieving a high-speed data transmission in mobile wireless communication systems. Conventionally, fast Fourier transform that is the main signal processing of OFDM is implemented using digital signal processing. The DSP FFT LSI requires large power consumption. Current-mode FFT LSI with analog signal processing is one of the best solutions for high speed and low power consumption. However, for the operation of current-mode FFT LSI that has the structure of parallel-input and parallel-output, current-mode serial-to-parallel and parallel-to-serial converter are indispensable. We propose a novel current-mode SPC and PSC and full chip simulation results agree with experimental data. The proposed current-mode SPC and PSC promise the wide application of the current-mode analog signal processing in the field of low power wireless communication LSI.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.35-42
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• 2006

In this paper we implement a new simulator for performance analysis of a parallel digital signal processing distributed shared memory multiprocessor systems. using Parsec The key idea of this simulator is suitable in simulation of system that uses DMA function of TMS320C6701 DSP chip and local memory which have fast access time. Also, because correction of performance parameter and reconfiguration for hardware components are easy, we can analyze performance of system in various execution environments. In the simulation, FET, 2D FET, Matrix Multiplication. and Fir Filter, which are widely used DSP algorithms. have been employed. Using our simulator, the result has been recorded according to different the number of processor, data sizes, and a change of hardware element. The performance of our simulator has been verified by comparing those recorded results.

• Journal of Mechanical Science and Technology
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• v.20 no.9
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• pp.1410-1417
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• 2006

The metal processing system usually consists of various components such like motors, work rolls, backup rolls, idle rolls, sensors, etc. Even a simple fault in a single component in the system may cause a serious damage on the final product. It is therefore necessary to diagnose the faults of the components to detect and prevent system failure. Especially, the defects in a work roll are critical to the quality of strip. It is especially difficult to detect faults of a roll by using the existing frequency analysis method if the speed of the roll is changing. In this study, a new diagnosis method for roll eccentricity under the roll speed changes was developed. The new method was induced from analyzing the rolling mechanism by using rolling force models, radius-speed relationship, and measured rolling force, etc. Simulation results by using the field data show that the proposed method is very useful.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.5
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• pp.612-619
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• 2013

This paper proposes an early diagnosis technique for the stator-turn fault (STF) in an interior permanent magnet (IPM)-type brushless DC (BLDC) motor using the impedance parameter. We have analyzed the varying characteristics owing to the STF through various experiments and the finite element method (FEM). As a result, we have presented a simple method for fault detection. This technique can be applied without requiring a fast Fourier transform (FFT) and the calculation of the negative-sequence impedance. The fault detection system works on the basis of the comparison the measured impedance with the database impedance. The variations in the characteristics owing to the STF as well as the proposed technique have been verified through the simulation and experiment.