• Proceedings of the KIEE Conference
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• 1999.07e
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• pp.2311-2313
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• 1999

웨이블렛 기법은 비주기적 신호의 해석에 있어 새롭게 적용되고 있는 방법이다. 이 방법은 Fourier Transform(FT), the Fast Fourier Transform(FFT), Least Square Method 방법과는 달리 시간 -주파수 분석을 통해 비주기적 과도 신호의 감지와 특징 추출이 용이하다. 이에 본 연구에서는 이러한 통계적 기법과는 달리 부분 방전 발생 신호를 시간-주파수 영역에서 연속적으로 분석 가능한 웨이블렛 기법을 이용하여 시간에 따른 절연체의 열화를 해석 및 진단하기로 한다. 부분 방전 현상을 나타내는 데이터는 방대하므로 진단을 위해 해석 정보에서 특정한 특징을 추출하며 이를 바탕으로 체계화된 데이터 베이스를 구성하는 기반을 마련한다. 해석에 필요한 신호는 복합감지 시스템(부분방전 시스템, 음향방출 시스템)을 이용하여 수집하였다.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.559-568
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• 2017

Harmonic/inter-harmonic detection and analysis is an important issue in power system signal processing. This paper proposes a fast algorithm based on matching pursuit (MP) sparse signal decomposition, which can be employed to extract the harmonic or inter-harmonic components of a distorted electric voltage/current signal. In the MP iterations, the method extracts harmonic/inter-harmonic components in order according to the spectrum peak. The Fast Fourier Transform (FFT) and nonlinear optimization techniques are used in the decomposition to realize fast and accurate estimation of the parameters. First, the frequency estimation value corresponding to the maxim spectrum peak in the present residual is obtained, and the phase corresponding to this frequency is searched in discrete sinusoids dictionary. Then the frequency and phase estimations are taken as initial values of the unknown parameters for Nelder-Mead to acquire the optimized parameters. Finally, the duration time of the disturbance is determined by comparing the inner products, and the amplitude is achieved according to the matching expression of the harmonic or inter-harmonic. Simulations and actual signal tests are performed to illustrate the effectiveness and feasibility of the proposed method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.361-364
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• 1995

Wavelet Transform is a new tools for signal processing, such as data compressing extraction of parameter for Reconition and Diagnostics. This transform has an advandage of a good resolution compared to Fast Fourier Transform (FFT) In this study, we employ the wavelet transform for analysis of Acoustic Emission raw signal generated form rotary compressor. In abnormal condition of rotary compressor, the state of operating condition can be classified by analizing coefficient of wavelet transformed signal.

• Journal of Korean Ophthalmic Optics Society
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• v.10 no.4
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• pp.305-312
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• 2005

In this thesis, Lohmann's algorithm and FFT (fast Fourier transform) are used to synthesize binary-phase holograms. FFT computing is carried out for the calculation of complex wavefronts of $128{\times}128$ sampling points of an object that is numerically specified. Then using the Lohmann's algorithm, the amplitude and the phase of complex wavefronts are encoded in binary holograms on each sampling points. PC (personal computer) and laser printer are used to plot binary-phase holograms and CGH (computer generated holograms) films are obtained from this plot by photographic reduction. Holographic images of numerically specified objects are reconstructed from the He-Ne laser and the inverse Fourier optics system. We estimate the quality of holographic images according to the sampling number, application of random phase, amplitude clipping and bleaching the CGH film. We derive optimized conditions to reconstruct better holographic images and to reduce the speckle noise. FFT and Lohmann's algorithm are implemented with MS Visual BASIC 6.0 for the programming of binary-phase hologram.

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.2
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• pp.237-242
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• 2011

This paper proposes a detection algorithm for each section which detects the voiced section, unvoiced section, and the silence section at each frame using a multi-layer perceptron neural network. First, a power spectrum and FFT (fast Fourier transform) coefficients obtained by FFT are used as the input to the neural network for each frame, then the neural network is trained using these power spectrum and FFT coefficients. In this experiment, the performance of the proposed algorithm for detection of the voiced section, unvoiced section, and silence section was evaluated based on the detection rates using various speeches, which are degraded by white noise and used as the input data of the neural network. In this experiment, the detection rates were 92% or more for such speech and white noise when training data and evaluation data were the different.

• The Journal of the Acoustical Society of Korea
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• v.19 no.3
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• pp.86-91
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• 2000

In this paper, we will discuss the characteristics of the magnitude and the phase of the piano sound in frequency domain by using the FFT(Fast Fourier Transform). The method deciding the parameters representing those sounds through the mathematical model is described. We used the curve fitting method for the modeling of the harmonic part of the sound including the fundamental frequency in order to minimize the errors between original sounds and modeled sounds. furthermore, we used the line segment approximation method for the modeling of the noise part around fundamental frequency. We also applied the same method for the phase model and could get the modeled sound to be similar to the original sound using the parameters. Therefore the high compression ratio comparing the modeled sound to the original sound is achieved.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.10 no.3
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• pp.167-172
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• 2010

In this paper, we analyze and simulate the performance of a pilot signal detection algorithm based on fast Fourier transform (FFT) for several system parameters in order to detect advanced television system committee digital television (ATSC DTV) signals. Requirements for detecting DTV signals are analyzed. And the detection performance is compared according to sensing frequency and time. Form the simulation results, it is confirmed that the signal detection performance increases as the sensing frequency rises. The results of this paper can be applied for implementing cognitive radio (CR) systems in the frequency band of DTV signals.

• Journal of the Korean Society for Nondestructive Testing
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• v.28 no.4
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• pp.372-376
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• 2008

We report experimental results on the correlations between welding penetration depth and the frequencies of the radiation from the welding pool. Various welding samples such as SUS304, brass, SUS316, etc. have been investigated with 2 kW CW Nd:YAG laser welding machine. The radiation signals from the plume generated by the interactions between the welding sample and laser with respect to the defocusing length was measured with fiber system collecting the plume signal. Analysis of the frequencies by using fast Fourier transform (FFT) shows that the penetration depth is deep as plume signal frequencies are low, shallow penetration depth for high frequencies. Frequencies up to 250 Hz for obtained signals can be analyzed with the discrete FFT. This is the useful method fur closed loop control of the laser power with respect to the welding penetration depth and is used for real time inspection of the welding quality.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.659-665
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• 2017

In this paper, a low complexity fast Fourier transform(FFT) processor is proposed for multiple input multiple output(MIMO) systems. The IEEE 802.11ac standard has been adopted along with the demand for a system capable of high channel capacity and Gbps transmission in order to utilize various multimedia services using a wireless LAN. The proposed scalable FFT processor can support the variable length of 64, 128, 256, and 512 for 8x8 antenna configuration as specified in IEEE 802.11ac standard with MIMO-OFDM scheme. By reducing the required number of non-trivial multipliers with mixed-radix(MR) and multipath delay commutator(MDC) architecture, the complexity of the proposed FFT processor was dramatically decreased. Implementation results show that the proposed FFT processor can reduced the logic gate count by 50%, compared with the radix-2 SDF FFT processor. Also, compared with the 8-channel MR-2/2/2/4/2/4/2 MDC processor and 8-channel MR-2/2/2/8/8 MDC processor, it is shown that the gate count is reduced by 18% and 17% respectively.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.5
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• pp.32-38
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• 2009

FTT(Fast Fourier Transform) processor is widely used in OFDM(Orthogonal Frequency Division Multiplesing) system. Because of the increased requirement of mobility and bandwidth in the OFDM system, they need large point FTT processor. Since the size of memory which stores the twiddle factor coefficients are proportional to the N of FFT size, we propose a new method by which we can reduce the size of the coefficient memory. In the proposed method, we exploit a counter and unsigned multiplier to generate the twiddle factor indices. To verify the proposed algorithm, we design TFCGs(Twiddle Factor Coefficient Generator) for 1024pint FFTs with R2SDF(Radix-2 Single-Path Delay Feedback), $R2^3SDF,\;R2^3SDF,\;R2^4SDF$ architectures. The size of ROM is reduced to 1/8N. In the case of $R2^4SDF$ architecture, the area and the power are reduced by 57.9%, 57.5% respectively.