• The Journal of the Acoustical Society of Korea
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• v.23 no.1
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• pp.24-29
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• 2004

In ocean acoustic tomography (OAT), the pulse compression techniques using M-sequences are employed in the many studies for investigating the ocean structures. M-sequences can provide the good time and Doppler resolution in the process of demodulation using matched-filter. The signal-to-noise (SNR) performance at the output of receiver may be improved by manipulating received signal, i. e. coherently averaging. The processing time can be significantly reduced by using fast hadarmard transform (FHT) or fast Fourier transform (FFT). In this paper, we estimate the multipath arrival structures and delay times using the East Korean Sea experiment data and explore the compensation method for the detrimental effects on performance due to sampling rate error. We also analyze the characteristics of the ocean acoustic channels through scattering function, delay power profile, and time dispersions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.1
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• pp.83-95
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• 1999

Wavelet transform has localization for time or frequency. It is useful to analyze a nonstationary signal. Basic function on wavelet transform is generated dilating and translating the original wavelet(mother wavelet). In this paper, time-frequency analysis method using linear combination wavelet transform is proposed. And it is applied to diagnostic monitoring system using the proposed linear combination wavelet transform. The stationary and nonstationary signal is used linear chirp signal, fan noise signal, a sinusoid signal from revolution body, electronic signal. Transform applied to signal analysis use fast Fourier transform (FFT), Daubechies, Haar and proposed linear combination method. The result of time-frequency analysis using linear combination wavelet transform is suited for portraying nonstationary time signal as well as stationary signal. Also the diagnostic monitoring system carry out the effective the signal analysis.

• International Journal of Highway Engineering
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• v.16 no.5
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• pp.59-66
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• 2014

PURPOSES : This study is to predict the Sound Pressure Level(SPL) obtained from the Noble Close ProXimity(NCPX) method by using the Extended Kalman Filter Algorithm employing the taylor series and Linear Regression Analysis based on the least square method. The objective of utilizing EKF Algorithm is to consider stochastically the effect of error because the Regression analysis is not the method for the statical approach. METHODS : For measuring the friction noise between the surface and vehicle's tire, NCPX method was used. With NCPX method, SPL can be obtained using the frequency analysis such as Discrete Fourier Transform(DFT), Fast Fourier Transform(FFT) and Constant Percentage Bandwidth(CPB) Analysis. In this research, CPB analysis was only conducted for deriving A-weighted SPL from the sound power level in terms of frequencies. EKF Algorithm and Regression analysis were performed for estimating the SPL regarding the vehicle velocities. RESULTS : The study has shown that the results related to the coefficient of determination and RMSE from EKF Algorithm have been improved by comparing to Regression analysis. CONCLUSIONS : The more the vehicle is fast, the more the SPL must be high. But in the results of EKF Algorithm, SPLs are irregular. The reason of that is the EKF algorithm can be reflected by the error covariance from the measurements.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.23 no.1
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• pp.116-124
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• 2009

This paper proposes a new Artificial-Intelligent(AI) Power Quality(PQ) diagnosis algorithm using Discrete Wavelet Transform(DWT), Fast Fourier Transform(FFT), Root-Mean-Square(RMS) value. The developed algorithm is able to detect and classify the PQ problems such as the transient, the voltage sag, the voltage swell, the voltage interruption and the total harmonics distortion. The 15.36[kHz] sampling frequency is used to measure the voltages in a power system. The measured signals are used for DWT, FFT, RMS calculation. For AI diagnosis of the PQ problems, a simple multi-layered Artificial Neural Network(ANN) with the back-propagation algorithm is adopted, programmed in C++ and tested in PSIM simulation studies. Finally, the algorithm, which is installed in MP PQ+256 with TI DSP320C6713, is proved to diagnose the PQ problems efficiently.

• ETRI Journal
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• v.8 no.1
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• pp.3-5
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• 1986

본 고는 image의 pattern을 identify하기 위해 그 image data의 FFT(Fast Fourier Transform)를 취한 후 에너지 스펙트럼의 크기를 폐적분한 값으로 부터 original input object와 비교대상의 object에 대한 mean square error 값의 차이를 시뮬레이션한 결과 얻은 threshold value와 비교함으로써 matching 을 구현하기 위함이다. Vax11-780/vms와 Fortran77 Language를 사용하여 시뮬레이션을 수행하였으며 Tektronix graphic terminal이 digitized된 이미지의 모니터용으로 사용되었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2012.10a
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• pp.597-599
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• 2012

음성인식 및 음성신호처리 분야에서 신경회로망은 음성인식의 카테고리 분류에 주로 이용되고 있다는 점에 착안하여, 본 논문에서는 신경회로망의 입력신호로 음성의 진폭 스펙트럼 및 위상 스펙트럼을 사용한 잡음억제를 위한 신경회로망을 제안한다. 본 논문에서 제안한 알고리즘은 고속 푸리에 변환(Fast Fourier Transform, FFT)에 의한 진폭 스펙트럼 및 위상 스펙트럼을 사용한 잡음억제 신경회로망을 이용하여 각 프레임에서 FFT 스펙트럼을 추정한다.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 2003.11a
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• pp.384-387
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• 2003

The object of the present work is the analysis of head/disk interaction during start/stop and constant speed operation using acoustic emission (AE). The frequency spectrum analysis is performed using the AE signal obtained during the head/disk interaction. The FFT (Fast Fourier Transform) analysis of the AE signals is used to understand the interaction between the AE signal and the state of contact.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1999.11a
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• pp.383-387
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• 1999

인간의 감성을 고려하는 제품의 생산에서 촉감은 인간이 제품을 만질 때 직접적으로 느낄 수 있는 중요한 감각이다. 이러한 촉감의 연구를 위해 직물을 대상으로 직물 표면의 거칠기를 측정하고 해석하였다. 측정된 표면 거칠기를 Fast Fourier Transform 변환하여 직물구조를 분석하는 기준으로 하였다. 각 peak 값들을 분석하여 나온 값이 직물 구조를 수식화하여 사용할 수 있는 좋은 방법이 됨을 알았다. 또한, 실의 잔털량을 측정하여, 잔털량과 인간의 주관적인 감각을 대표하는 값과의 상관관계를 조사하였다. 잔털량이 인간의 주관적인 감각을 객관적으로 표현할 수 있는 한 요소로 사용될 수 있다는 것을 확인하였다.

• ETRI Journal
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• v.30 no.3
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• pp.451-460
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• 2008

Recently, the power consumption of integrated circuits has been attracting increasing attention. Many techniques have been studied to improve the power efficiency of digital signal processing units such as fast Fourier transform (FFT) processors, which are popularly employed in both traditional research fields, such as satellite communications, and thriving consumer electronics, such as wireless communications. This paper presents solutions based on parallel architectures for high throughput and power efficient FFT cores. Different combinations of hybrid low-power techniques are exploited to reduce power consumption, such as multiplierless units which replace the complex multipliers in FFTs, low-power commutators based on an advanced interconnection, and parallel-pipelined architectures. A number of FFT cores are implemented and evaluated for their power/area performance. The results show that up to 38% and 55% power savings can be achieved by the proposed pipelined FFTs and parallel-pipelined FFTs respectively, compared to the conventional pipelined FFT processor architectures.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.1
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• pp.37-41
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• 2014

FFT (Fast Fourier Transform) has been widely used in various fields such as image processing, voice processing, physics, astronomy, applied mathematics and so forth. Much research has been conducted due to the importance of the FFT and recently new FFT algorithms using a GPU (Graphics Processing Unit) have been developed for the purpose of much faster processing. In this paper, the new optimal FFT algorithm using the Pease FFT algorithm has been proposed reflecting the hardware configuration of a GPGPU (General Purpose computing of GPU). According to the experiments, the proposed algorithm outperformed by between 3% to 43% compared to the CUFFT algorithm.