• Title/Summary/Keyword: Frequency Domain Decomposition

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Design of 2-D Separable Denominator Digital Filters based on the reduced Dimension Decomposition of Frequency Domain Specification (주파수영역 설계명세조건의 저차원분해를 이용한 2차원 디지털 필터의 설계)

  • 문용선
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.5 no.7
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    • pp.1346-1353
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    • 2001
  • This paper presents an algorithm for the design of 2 dimension separable denominator digital filter(SDDF). The proposed algorithm is based on the reduced dimensional decomposition not only 2 dimension SDDF's but also of given 2 dimension specification. The frequency domain design of 2 dimension separable denominator digital filters based on the reduced dimensional decomposition can be realized when the given 2 dimension frequency specification are optimally decomposed into a pair of 1 dimension digital filter specification via singular value decomposition. the algorithm is computationally efficient and numerically stable. In case of the low pass filter, the approximation error of the proposed design algorithm is $e_{m}$=5.17, $e_{r1}$ =8.78, $e_{r2}$=7.34, while in case of band pass filter, the approximation error is $e_{m}$=13.00, $e_{r1}$=62.76, $e_{r2}$=62.7676.7676

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Influence of asphalt removal on operational modal analysis of Egebækvej Bridge

  • Umut Yildirim
    • Smart Structures and Systems
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    • v.31 no.2
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    • pp.171-181
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    • 2023
  • Using the most up-to-date system identification methods in both time and frequency domains, the dynamic monitoring data from the reinforced concrete Egebaekvej Bridge near Holte, Denmark, is examined in this investigation. The bridge was erected in the 1960s and was still standing during test campaign before demolishing. The ARTeMIS Modal was adopted to derive the modal parameters from ambient vibration data. Several Operational Modal Analysis (OMA) approaches were applied, including Enhanced Frequency Domain Decomposition (EFDD), Curve-fit Frequency Domain Decomposition (CFDD), and Frequency Domain Decomposition (FDD). Afterward, Principal Component (SSI-PC), Unweighted Principal Component (SSI-UPC) Stochastic Subspace Identification methods were utilized. Danish engineering consulting company, COWI with the allowance of the bridge contractor BARSLUND, allow the researcher for this experimental test to demonstrate the impact of OMA applications.

Decomposition of Speech Signal into AM-FM Components Using Varialle Bandwidth Filter (가변 대역폭 필터를 이용한 음성신호의 AM-FM 성분 분리에 관한 연구)

  • Song, Min;Lee, He-Young
    • Speech Sciences
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    • v.8 no.4
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    • pp.45-58
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    • 2001
  • Modulated components of a speech signal are frequently used for speech coding, speech recognition, and speech synthesis. Time-frequency representation (TFR) reveals some information about instantaneous frequency, instantaneous bandwidth and boundary of each component of the considering speech signal. In many cases, the extraction of AM-FM components corresponding to instantaneous frequencies is difficult since the Fourier spectra of the components with time-varying instantaneous frequency are overlapped each other in Fourier frequency domain. In this paper, an efficient method decomposing speech signal into AM-FM components is proposed. A variable bandwidth filter is developed for the decomposition of speech signals with time-varying instantaneous frequencies. The variable bandwidth filter can extract AM-FM components of a speech signal whose TFRs are not overlapped in timefrequency domain. Also, amplitude and instantaneous frequency of the decomposed components are estimated by using Hilbert transform.

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Review of Data-Driven Multivariate and Multiscale Methods

  • Park, Cheolsoo
    • IEIE Transactions on Smart Processing and Computing
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    • v.4 no.2
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    • pp.89-96
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    • 2015
  • In this paper, time-frequency analysis algorithms, empirical mode decomposition and local mean decomposition, are reviewed and their applications to nonlinear and nonstationary real-world data are discussed. In addition, their generic extensions to complex domain are addressed for the analysis of multichannel data. Simulations of these algorithms on synthetic data illustrate the fundamental structure of the algorithms and how they are designed for the analysis of nonlinear and nonstationary data. Applications of the complex version of the algorithms to the synthetic data also demonstrate the benefit of the algorithms for the accurate frequency decomposition of multichannel data.

Construction stage effect on the dynamic characteristics of RC frame using operational modal analysis

  • Arslan, Mehmet Emin;Durmus, Ahmet
    • Computers and Concrete
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    • v.12 no.1
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    • pp.79-90
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    • 2013
  • In this study, dynamic characteristics such as natural frequencies, mode shapes and damping ratios of RC frame is determined for different construction stages using Operational Modal Analyses method under ambient vibration. Full scaled, one bay and one story RC frames are selected as an application for different construction stages such as plane, brick in-filled and brick in-filled with plaster. The RC frame is vibrated by natural excitations with small impact effects and the response signals are measured using sensitive accelerometers during ambient vibration tests. Measurement time-frequency span and effective mode number are determined by considering similar studies in literature. Sensitive seismic accelerometers are used to collect signals obtained from the experimental tests. To obtain experimental dynamic characteristics, output-only system identification technique is employed namely; Enhanced Frequency Domain Decomposition technique in the frequency domain. It is demonstrated that the ambient vibration measurements are enough to identify the most significant modes of RC frames.

Realization of Variable Bandwidth Filter for Decomposition of Speech Signals into AM-FM Components (음성신호의 AM-FM 성분 분리를 위한 가변대역폭 필터 구현)

  • 이희영;김용태
    • Proceedings of the IEEK Conference
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    • 2003.07e
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    • pp.2208-2211
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    • 2003
  • In this paper, a variable bandwidth filter(VBF) is realized with the purpose of the decomposition of speech signals with time-varying instantaneous of frequencies. The proposed VBF can extract AM-FM components of a speech signal whose time-frequency representations(TFRs) are not overlapped in time-frequency domain

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Comparative study on modal identification methods using output-only information

  • Yi, Jin-Hak;Yun, Chung-Bang
    • Structural Engineering and Mechanics
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    • v.17 no.3_4
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    • pp.445-466
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    • 2004
  • In this paper, several modal identification techniques for output-only structural systems are extensively investigated. The methods considered are the power spectral method, the frequency domain decomposition method, the Ibrahim time domain method, the eigensystem realization algorithm, and the stochastic subspace identification method. Generally, the power spectral method is most widely used in practical area, however, the other methods may give better estimates particularly for the cases with closed modes and/or with large measurement noise. Example analyses were carried out on typical structural systems under three different loading cases, and the identification performances were examined throught the comparisons between the estimates by various methods.

Image Enhancement Using Homomorphic Transformation and Multiscale Decomposition (호모모프변환과 다중 스케일 분해를 이용한 영상향상)

  • Ahn, Sang-Ho;Kim, Ki-Hong;Kim, Young-Choon;Kwon, Ki-Ryong;Seo, Yong-Su
    • Journal of Korea Multimedia Society
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    • v.7 no.8
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    • pp.1046-1057
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    • 2004
  • An image enhancement method using both homomorphic transformation and multiscale decomposition is proposed. The original image is first transformed to homomorphic domain by taking the logarithm, is then separated to multiscales. These multiscales are combined with weighting. The combined signal is exponentially transformed back into intensity domain. In homomorphic domain, the magnitude control of low frequency component make change the dynamic range, and the magnitude control of the other frequency components contribute to enhancement of the contrast. The "${\AA}$ trous" algorithm, which has a simple and efficient scheme, is used for multiscale decomposition. The performance of proposed method is verified by simulation.

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A study on the proper orthogonal decomposition of the structural dynamic system (구조진동시스템의 적합직교분해에 관한 연구)

  • Baek, Sung-Min;Cho, Maeng-Hyo
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2010.04a
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    • pp.171-174
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    • 2010
  • 적절한 근사화 과정을 통하여 구축된 축소 시스템은 전체 시스템의 거동을 적은 수의 정보를 통하여 효과적으로 표현할 수 있다. 효과적인 시스템 축소를 위하여 본 연구에서는 주파수 영역 Karhunen-Loeve (Frequency-domain Karhunen-Loeve, FDKL) 기법과 시스템 등가 확장 축소 과정(System equivalent expansion reduction process, SEREP)을 연동한 축소 기법을 제안한다. 적합직교분해(Proper orthogonal decomposition)의 한 방법인 FDKL기법을 통하여 최적모드(Optimal mode)를 구하고 이에 SEREP을 적용하여 자유도 변환 행렬을 구한다. 이때 주자유도 선정은 2단계 축소기법을 적용한다. 최종적으로 제안된 기법은 수치예제를 통하여 검증한다.

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Modal tracking of seismically-excited buildings using stochastic system identification

  • Chang, Chia-Ming;Chou, Jau-Yu
    • Smart Structures and Systems
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    • v.26 no.4
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    • pp.419-433
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    • 2020
  • Investigation of structural integrity has been a critical issue in the field of civil engineering for years. Visual inspection is one of the most available methods to explore deteriorative components in structures. Still, this method is not applicable to invisible damage of structures. Alternatively, system identification methods are capable of tracking modal properties of structures over time. The deviation of these dynamic properties can serve as indicators to access structural integrity. In this study, a modal tracking technique using frequency-domain system identification from seismic responses of structures is proposed. The method first segments the measured signals into overlapped sequential portions and then establishes multiple Hankel matrices. Each Hankel matrix is then converted to the frequency domain, and a temporal-average frequency-domain Hankel matrix can be calculated. This study also proposes the frequency band selection that can divide the frequency-domain Hankel matrix into several portions in accordance with referenced natural frequencies. Once these referenced natural frequencies are unavailable, the first few right singular vectors by the singular value decomposition can offer these references. Finally, the frequency-domain stochastic subspace identification tracks the natural frequencies and mode shapes of structures through quick stabilization diagrams. To evaluate performance of the proposed method, a numerical study is carried out. Moreover, the long-term monitoring strong motion records at a specific site are exploited to assess the tracking performance. As seen in results, the proposed method is capable of tracking modal properties through seismic responses of structures.