• Journal of The Korean Astronomical Society
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• v.37 no.5
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• pp.349-353
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• 2004

Magnetic fields are an important ingredient of galaxy clusters and are indirectly observed on cluster scales as radio haloes and radio relics. One promising method to shed light on the properties of cluster wide magnetic fields is the analysis of Faraday rotation maps of extended extragalactic radio sources. We developed a Fourier analysis for such Faraday rotation maps in order to determine the magnetic power spectra of cluster fields. In an advanced step, here we apply a Bayesian maximum likelihood method to the RM map of the north lobe of Hydra A on the basis of our Fourier analysis and derive the power spectrum of the cluster magnetic field. For Hydra A, we measure a spectral index of -5/3 over at least one order of magnitude implying Kolmogorov type turbulence. We find a dominant scale of about 3 kpc on which the magnetic power is concentrated, since the magnetic autocorrelation length is ${\lambda}_B = 3 {\pm} 0.5\;kpc$. Furthermore, we investigate the influences of the assumption about the sampling volume (described by a window function) on the magnetic power spectrum. The central magnetic field strength was determined to be ${\~}7{\pm}2{\mu}G$ for the most likely geometries.

• The Journal of the Acoustical Society of Korea
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• v.13 no.6
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• pp.66-74
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• 1994

Simulation of sonar reverberation time series is very useful because most acoustic models are power level models and have a difficulty when performance of hardware system is evaluated under the reverberant condition. Thus, in this paper, the simulation of reverberation time series is attempted, First, normalized spectrum, whose bandwidth is varying in the frequency domain and which has zero-mean Gaussian distribution, is calculated at pre-selected receiving time. Second, reverberation levels given by underwater acoustic model are combined with normalized spectrum in the frequency domain. Finally, nonstationary sonar reverberation time series are simulated by IFT(Inverse Fourier Transform).

• Journal of Korean Association for Spatial Structures
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• v.4 no.2 s.12
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• pp.81-88
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• 2004

The dynamic instability of snapping phenomena has been studied by many researchers. Few papers deal with dynamic buckling under loads with periodic characteristics, and the behavior under periodic excitations is expected to be different from behavior under STEP excitations. We investigate the fundamental mechanisms of the dynamic instability when the sinusoidally shaped arch structures are subjected to sinusoidally distributed excitations with pin-ends. The mechanisms of dynamic indirect snapping of shallow arches are especially investigated under not only STEP function excitations but also under sinusoidal harmonic excitations, applied i the up-and-down direction. The dynamic nonlinear responses are obtained by the numerical integration of the geometrically nonlinear equation of motion. And using this analyze characteristics of the dynamic instability through the running response spectrum by FFT(Fast Fourier Transform).

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.288-290
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• 1999

In view of the importance of DFT(Discrete Fourier Transform) in spectrum analysis, its computation efficiency is a topic. This paper presents calculation time to extract the power frequency at a fault signal using DFT. Furthermore, it is tested a relaying algorithm based on modified DFT and its application to Micro-controller.

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.1021-1024
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• 2000

본 논문에서는 영상 인식 기법 중의 하나인 UNL Transform 기법을 적용해서 RF 특성을 분석해 보았다. 이 특성 분석기를 바탕으로 RF PBA단의 진단기를 개발하는 과정을 보이고 있다.

• Proceedings of the KIEE Conference
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• 1987.07a
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• pp.86-89
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• 1987

In this paper, feature vectors composed of 6 features of Fourier spectrum of 2-D image at each projection angle and 7 features of invariant moments are defined. The feature are extracted by optical Fourier transformer and Radon transformer. After extracting the feature, the input pattern is recognized using the squared Mahalanobis distance.

• Journal of the Korean Society of Radiology
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• v.12 no.4
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• pp.491-496
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• 2018

The purpose of this study is to analyze the noise spectra in DWI (diffusion-weighted imaging) pulse sequences of 1.5 Tesla and 3.0 Tesla MRI, The ACR (American College of Radiology) phantom and noise spectrum were analyzed by FFT (fast Fourier transform) and TFFT (temporal frequency analysis) using WavePad sound editor version 8.13 (NCH software, Greenwood Village, CO, USA). Noise spectra, FFT and TFFT were analyzed for laboratory 1.5Tesla and 3.0Tesla DWI MR pulse sequences. The noise threshold of the frequency amplitude in the FFT and TFFT at 3.0Tesla compared to 1.5Tesla was between 1.5Tesla and -6 dB, and between 3.0Tesla and 0 dB, the DWI pulse sequence for the patient's noise reduction was appropriately MR examination needs to be applied.

• Journal of the Korea Society of Computer and Information
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• v.15 no.12
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• pp.19-26
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• 2010

In this paper, we studied about the Embedded System of the biosignal measurement and analysis to sensibility evaluation in daily life for non-intrusive. This system is two kinds of measuring biosiganls(Electrocardiogram:ECG, Photoplethysmography:PPG) and analyzed by real-time wireless transmission to notebook PC using bluetooth for consistent and reliability of physiological way to assess continuously changing sensibility. Comparative studied of an autonomic nerve system activity ratio on characteristics frequency band of two kinds of biosignal analyzed frequency way using the Fast Fourier Transform(FFT) and Power Spectrum Density(PSD). Also the key idea of this system is to minimize computing of analysis algorithm for faster and more accurate to assess the sensibility, and the result of the visualization using graph. In this paper, we evaluated the analysis system to assess sensibility that measuring various situation in daily life using a non-intrusive biosignal measurement system, and the accuracy and reliability in comparison with difference of result by development analysis system.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1996.10a
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• pp.211-214
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• 1996

This paper propose a method for pattern recogniton using spectrum analyzer and fuzzy ARTMAP. Contour sequences obtained from 2-D planar images represent the Euclidean distance between the centroid and all boundary pixels of the shape, and are related to the overall shape of the images. The Fourier transform of contour sequence and spectrum analyzer are used as a means of feature selection and data reduction. The three dimensional spectral feature vectors are extracted by spectrum analyzer from the FFT spectrum. These Spectral feature vectors are invariant to shape translation, rotation, and scale transformations. The fuzzy ARTMAP neural network which is combined with two fuzzy ART modules is trained and tested with these feature vectors. The experiments include 4 aircrafts and 4 industrial parts recognition process are presented to illustrate the high performance of this proposed method in the ion problems of noisv shapes.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.2
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• pp.34-42
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• 1997

This paper deals with the recognition of closed planar shape using a three dimensional spectral feature vector which is derived from the FFT(Fast Fourier Transform) spectrum of contour sequence and fuzzy ARTMAP neural network classifier. Contour sequences obtained from 2-D planar images represent the Euclidean distance between the centroid and all boundary pixels of the shape, and are related to the overall shape of the images. The Fourier transform of contour sequence and spectrum analyzer are used as a means of feature selection and data reduction. The three dimensional spectral feature vectors are extracted by spectrum analyzer from the FFT spectrum. These spectral feature vectors are invariant to shape translation, rotation and scale transformation. The fuzzy ARTMAP neural network which is combined with two fuzzy ART modules is trained and tested with these feature vectors. The experiments including 4 aircrafts and 4 industrial parts recognition process are presented to illustrate the high performance of this proposed method in the recognition problems of noisy shapes.