• 제목/요약/키워드: Fourier Function

검색결과 612건 처리시간 0.033초

생물학적 모방에 따른 물고기 로봇의 직진유영 연구 (A study on the straight cruise of fish robot according to biological mimic)

  • 박진현;이태환;최영규
    • 한국정보통신학회논문지
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    • 제15권8호
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    • pp.1756-1763
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    • 2011
  • 본 연구에서는 생물학적 모방에 따른 물고기 로봇의 직진유영에 관한 연구로써, Liu 등이 제안한 꼬리 모션 함수를 푸우리에 급수 전개의 7차 항까지 고려한 제안된 방법과 일반적인 사인함수만으로 근사한 방법과 비교하여 모의실험 하였다. 일반적으로 로봇 물고기의 꼬리 링크의 길이가 길어지고 링크가 많을 경우, 로봇 물고기의 꼬리 모션 함수의 말단 회전 관절 궤적은 사인 함수의 모양과 매우 다르다. 그러므로 로봇 물고기의 꼬리 궤적을 단순한 푸우리에 급수 전개의 기본파 성분만으로 근사하기에는 문제가 있다. 제안된 방법과 일반적인 사인함수만으로 근사한 방법의 모의실험 결과 제안된 방법이 로봇 물고기의 추력과 속도에서 10%정도 뛰어남을 보였다.

박막에서 쌍곡선형 열전도 방정식에 의한 열전도 해석 (Analysis of Hyperbolic Heat Conduction in a Thin Film)

  • 정우남;이용호;조창주
    • 에너지공학
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    • 제8권4호
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    • pp.540-545
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    • 1999
  • 고전적인 Fourier 열전도 방정식은 극저온하에서 또는 아주 짧은 시간동안의 가열시 타당성이 없는 것으로 고려되었다. 이러한 조건하에서는 열전도파의 성질이 지배적이기 때문에 , 수정된 Fourier 법칙에 근거한 쌍곡선형 열전도 방정식이 도입되었다. 열전도에 대한 Fourier 모델과 쌍곡선형 열전도모델이 적분변환법과 함께 Green 함수방법을 이용하여 분되었다. 한쪽 표면에서 주기적인 표면가열을 하는 유한한 평판의 열유속 분포 및 온도분포의 해를 제시하였고 각가의 모델로부터 얻어진 결과를 서로 비교검토하였다. 쌍곡선형 열전도 방정식에서 유도된 열전도파는 매개물을 통해 전파되어 맞은편쪽의 단열표면에서 가열 표면쪽으로 반사하였으나 , 고전적인 Fourier 모델에 의한 열은 열적교란이 매개물의 전체에 걸쳐서 전달된 후 즉각적으로 무한한 속도로 열전파가 발생함을 보여주었다.

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IMPROVED STATIONARY $L_p$-APPROXIMATION ORDER OF INTERPOLATION BY CONDITIONALLY POSITIVE DEFINITE FUNCTIONS

  • Yoon, Jung-Ho
    • Journal of applied mathematics & informatics
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    • 제14권1_2호
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    • pp.365-376
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    • 2004
  • The purpose of this study is to show that the accuracy of the interpolation method can be at least doubled when additional smoothness requirements and boundary conditions are met. In particular, as a basis function, we are interested in using a conditionally positive definite function $\Phi$ whose generalized Fourier transform is of the form $\Phi(\theta)\;=\;F(\theta)$\mid$\theta$\mid$^{-2m}$ with a bounded function F > 0.

광역계통의 실시간해석을 위한 고속 저주파수 파라미터 추정 (Fast Estimation of Low Frequency Parameter for Real-Time Analysis in Wide Area Systems)

  • 김은주;심관식;김용구;김의선;남해곤;임영철
    • 전기학회논문지
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    • 제58권6호
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    • pp.1078-1086
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    • 2009
  • This paper presents a Fourier based algorithm for estimating the parameters of the low frequency oscillating modes. The proposed methods estimates various parameters(frequency, damping factor, mode magnitude, phase) by fitting Fourier spectrum and phase with a damped exponential cosine function. Dominant frequency is selected by taking frequency corresponding to the peak spectrum, and damping factor is estimated using the left/right spectra of Fourier spectrum. In addition, mode magnitude is calculated by the normalized peak spectrum, and phase is estimated from spectrum phase. Also, we introduce an accuracy index in order to determine the accuracy of the estimated parameters, and the index is calculated using the deviations of the peak spectrum and the left/right spectra. The parameter estimation methods proposed in this paper include very simple arithmetical processes, so the algorithms are simple and the calculation speed is very fast. The proposed methods are applied to test functions with two dominant modes. The results show that the proposed methods are highly applicable to low frequency parameter estimation.

Simulation of nonstationary wind in one-spatial dimension with time-varying coherence by wavenumber-frequency spectrum and application to transmission line

  • Yang, Xiongjun;Lei, Ying;Liu, Lijun;Huang, Jinshan
    • Structural Engineering and Mechanics
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    • 제75권4호
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    • pp.425-434
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    • 2020
  • Practical non-synoptic fluctuating wind often exhibits nonstationary features and should be modeled as nonstationary random processes. Generally, the coherence function of the fluctuating wind field has time-varying characteristics. Some studies have shown that there is a big difference between the fluctuating wind field of the coherent function model with and without time variability. Therefore, it is of significance to simulate nonstationary fluctuating wind field with time-varying coherent function. However, current studies on the numerical simulation of nonstationary fluctuating wind field with time-varying coherence are very limited, and the proposed approaches are usually based on the traditional spectral representation method with low simulation efficiency. Especially, for the simulation of multi-variable wind field of large span structures such as transmission tower-line, not only the simulation is inefficient but also the matrix decomposition may have singularity problem. In this paper, it is proposed to conduct the numerical simulation of nonstationary fluctuating wind field in one-spatial dimension with time-varying coherence based on the wavenumber-frequency spectrum. The simulated multivariable nonstationary wind field with time-varying coherence is transformed into one-dimensional nonstationary random waves in the simulated spatial domain, and the simulation by wavenumber frequency spectrum is derived. So, the proposed simulation method can avoid the complicated Cholesky decomposition. Then, the proper orthogonal decomposition is employed to decompose the time-space dependent evolutionary power spectral density and the Fourier transform of time-varying coherent function, simultaneously, so that the two-dimensional Fast Fourier transform can be applied to further improve the simulation efficiency. Finally, the proposed method is applied to simulate the longitudinal nonstationary fluctuating wind velocity field along the transmission line to illustrate its performances.

Rapid discrimination of commercial strawberry cultivars using Fourier transform infrared spectroscopy data combined by multivariate analysis

  • Kim, Suk Weon;Min, Sung Ran;Kim, Jonghyun;Park, Sang Kyu;Kim, Tae Il;Liu, Jang R.
    • Plant Biotechnology Reports
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    • 제3권1호
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    • pp.87-93
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    • 2009
  • To determine whether pattern recognition based on metabolite fingerprinting for whole cell extracts can be used to discriminate cultivars metabolically, leaves and fruits of five commercial strawberry cultivars were subjected to Fourier transform infrared (FT-IR) spectroscopy. FT-IR spectral data from leaves were analyzed by principal component analysis (PCA) and Fisher's linear discriminant function analysis. The dendrogram based on hierarchical clustering analysis of these spectral data separated the five commercial cultivars into two major groups with originality. The first group consisted of Korean cultivars including 'Maehyang', 'Seolhyang', and 'Gumhyang', whereas in the second group, 'Ryukbo' clustered with 'Janghee', both Japanese cultivars. The results from analysis of fruits were the same as of leaves. We therefore conclude that the hierarchical dendrogram based on PCA of FT-IR data from leaves represents the most probable chemotaxonomical relationship between cultivars, enabling discrimination of cultivars in a rapid and simple manner.

인공 지진 생성에서 Fourier 진폭 스펙트럼과 변수 추정을 위한 신경망 모델의 개발 (Development of Neural-Networks-based Model for the Fourier Amplitude Spectrum and Parameter Identification in the Generation of an Artificial Earthquake)

  • 조빈아;이승창;한상환;이병해
    • 한국전산구조공학회:학술대회논문집
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    • 한국전산구조공학회 1998년도 가을 학술발표회 논문집
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    • pp.439-446
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    • 1998
  • One of the most important roles in the nonlinear dynamic structural analysis is to select a proper ground excitation, which dominates the response of a structure. Because of the lack of recorded accelerograms in Korea, a stochastic model of ground excitation with various dynamic properties rather than recorded accelerograms is necessarily required. If all information is not available at site, the information from other sites with similar features can be used by the procedure of seismic hazard analysis. Eliopoulos and Wen identified the parameters of the ground motion model by the empirical relations or expressions developed by Trifunac and Lee. Because the relations used in the parameter identification are largely empirical, it is required to apply the artificial neural networks instead of the empirical model. Additionally, neural networks have the advantage of the empirical model that it can continuously re-train the new recorded data, so that it can adapt to the change of the enormous data. Based on the redefined traditional processes, three neural-networks-based models (FAS_NN, PSD_NN and INT_NN) are proposed to individually substitute the Fourier amplitude spectrum, the parameter identification of power spectral density function and intensity function. The paper describes the first half of the research for the development of Neural-Networks-based model for the generation of an Artificial earthquake and a Response Spectrum(NNARS).

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STFT와 RNN을 활용한 화자 인증 모델 (Speaker Verification Model Using Short-Time Fourier Transform and Recurrent Neural Network)

  • 김민서;문종섭
    • 정보보호학회논문지
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    • 제29권6호
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    • pp.1393-1401
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    • 2019
  • 최근 시스템에 음성 인증 기능이 탑재됨에 따라 화자(Speaker)를 정확하게 인증하는 중요성이 높아지고 있다. 이에 따라 다양한 방법으로 화자를 인증하는 모델이 제시되어 왔다. 본 논문에서는 Short-time Fourier transform(STFT)를 적용한 새로운 화자 인증 모델을 제안한다. 이 모델은 기존의 Mel-Frequency Cepstrum Coefficients(MFCC) 추출 방법과 달리 윈도우 함수를 약 66.1% 오버랩하여 화자 인증 시 정확도를 높일 수 있다. 새로운 화자 인증 모델을 제안한다. 이 때, LSTM 셀을 적용한 Recurrent Neural Network(RNN)라는 딥러닝 모델을 사용하여 시변적 특징을 가지는 화자의 음성 특징을 학습하고, 정확도가 92.8%로 기존의 화자 인증 모델보다 5.5% 정확도가 높게 측정되었다.

Saddlepoint approximations for the ratio of two independent sequences of random variables

  • Cho, Dae-Hyeon
    • Journal of the Korean Data and Information Science Society
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    • 제9권2호
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    • pp.255-262
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    • 1998
  • In this paper, we study the saddlepoint approximations for the ratio of independent random variables. In Section 2, we derive the saddlepoint approximation to the probability density function. In Section 3, we represent a numerical example which shows that the errors are small even for small sample size.

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REMARKS ON KERNEL FOR WAVELET EXPANSIONS IN MULTIDIMENSIONS

  • Shim, Hong-Tae;Kwon, Joong-Sung
    • Journal of applied mathematics & informatics
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    • 제27권1_2호
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    • pp.419-426
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    • 2009
  • In expansion of function by special basis functions, properties of expansion kernel are very important. In the Fourier series, the series are expressed by the convolution with Dirichlet kernel. We investigate some of properties of kernel in wavelet expansions both in one and higher dimensions.

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