• Title/Summary/Keyword: Spectrum estimation

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Experimental Study of Backscattered Underwater Signals from Multiple Scatterers (다중 산란체에 의한 수중 산란신호 실험연구)

  • Kim, Eunhye;Yoon, Kwan-seob;Jungyul Na
    • The Journal of the Acoustical Society of Korea
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    • v.23 no.1E
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    • pp.31-39
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    • 2004
  • Backscattered underwater signals from multiple scatterers contain information regarding resolvable spatial distribution of scatterers. This experimental study describes the spectral characteristics of backscattered signal from multiple scatterers, which are regularly or randomly spaced, in terms of their amplitude and phase and a proper signal analysis that will eventually provide scatterer spacing estimation. Air-filled tubes suspended in water, steel balls and plastic tubes buried in the sediment are the multiple scatterers. The cepstrum and the spectral autocorrelation (SAC) methods were used to estimate the scatterer spacing from the backscattered signals. It was found that the SAC method could be improved by employing singular value decomposition (SVD) to extract the effective rank for the spectral components. Unlike the conventional method of estimating the density of scatterers within the insonified volume of water, this type of estimation method would provide better understanding of the spatial distribution of scatterers in the ocean.

Structural Dynamic System Reconstruction (구조물 동적시스템 재현기법)

  • Kim, Hyeung-Yun
    • Journal of Institute of Control, Robotics and Systems
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    • v.8 no.4
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    • pp.308-312
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    • 2002
  • To determine the natural frequencies and damping ratios of composite laminated plates, we present an officient modal parameter estimation technique by developing residual spectrum based structural system reconstruction. The modal parameters can be estimated from poles and residues of the system transfer functions, derived from the state space system matrices. From vibration tests on cross-ply and angle-ply composite laminates, the natural frequencies and damping ratios can be estimated using the modal coordinates of the structural dynamic system reconstructed from the experimental frequency response functions. These results are compared with those of finite element analysis and single-degree-of-freedom curve fitting.

On the Center Pitch Estimation by using the Spectrum Leakage Phenomenon for the Noise Corrupted Speech Signals (배경 잡음하에서 스펙트럼 누설현상을 이용한 음성신호의 중심 피치 검출)

  • Kang, Dong-Kyu;Bae, Myung-Jin;Ann, Sou-Guil
    • The Journal of the Acoustical Society of Korea
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    • v.10 no.1
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    • pp.37-46
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    • 1991
  • The pitch estimation algorithms witch have proposed until now are difficult to detect wide range pitches regardless of age or sex. A little deviation are observed with reference to the center pitch in the distribution diagram of pitches, since pitches are characterized by a physical limitation of the coarticulation mechanism. If the center pitches are refered to the accurate pitch extraction procedure, the algorithms will be not only simplified in procedure but also improved in accuracy. In this paper, we proposed an algorithm that the center pitches are accurately detected by using the spectrum leakage phenomenon for the noise speech signals.

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A Study on Power Spectral Estimation of Background EEG with Pisarenko Harmonic Decomposition (Pisarenko Harmonic Decomposition에 의한 배경 뇌파 파워 스팩트럼 추정에 관한 연구)

  • Jeong, Myeong-Jin;Hwang, Su-Yong;Choe, Gap-Seok
    • Journal of Biomedical Engineering Research
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    • v.8 no.1
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    • pp.69-74
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    • 1987
  • The power spectrum of background EEG is estimated by the Plsarenko Harmonic Decomposition with the stochastic process whlch consists of the nonhamonic sinus Bid and the white nosie. The estimation results are examined and compared with the results from the maximum entropy spectral extimation, and the optimal order of this from the maximum entropy spectral extimation, and the optimal order of this model can be determined from the eigen value's fluctuation of autocorrelation of background EEG. From the comparing results, this method is possible to estimate the power spectrum of background EEG.

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Prediction of Highway Traffic Noise - Estimation of Sound Power Level Emitted by Vehicles (고속도로 교통소음 예측-자동차 주행소음의 음향파워레벨 평가)

  • 조대승;오정한;김진형;김성훈;최태묵;장태순;강희만;이성환
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.12 no.8
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    • pp.581-588
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    • 2002
  • Precise highway traffic noise simulation and reduction require the accurate data for sound power levels omitted by vehicles, varied to road surface, traffic speed, vehicle types and makers, different from countries to countries. In this study, we have elaboratively measured Korea highway traffic noise and parameters affecting noise levels at the nearside carriageway edge. From numerical simulation using the measured results for highway traffic noise, we propose not only two correction factors to enhance the accuracy of Korea highway traffic sound power estimation using ASJ Model-1998 but also its typical power spectrum according to road surface type. The measured and predicted highway traffic noise levels using the proposed sound power show little difference within 1 dB.

Noise Robust Speech Recognition Based on Noisy Speech Acoustic Model Adaptation (잡음음성 음향모델 적응에 기반한 잡음에 강인한 음성인식)

  • Chung, Yongjoo
    • Phonetics and Speech Sciences
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    • v.6 no.2
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    • pp.29-34
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    • 2014
  • In the Vector Taylor Series (VTS)-based noisy speech recognition methods, Hidden Markov Models (HMM) are usually trained with clean speech. However, better performance is expected by training the HMM with noisy speech. In a previous study, we could find that Minimum Mean Square Error (MMSE) estimation of the training noisy speech in the log-spectrum domain produce improved recognition results, but since the proposed algorithm was done in the log-spectrum domain, it could not be used for the HMM adaptation. In this paper, we modify the previous algorithm to derive a novel mathematical relation between test and training noisy speech in the cepstrum domain and the mean and covariance of the Multi-condition TRaining (MTR) trained noisy speech HMM are adapted. In the noisy speech recognition experiments on the Aurora 2 database, the proposed method produced 10.6% of relative improvement in Word Error Rates (WERs) over the MTR method while the previous MMSE estimation of the training noisy speech produced 4.3% of relative improvement, which shows the superiority of the proposed method.

Progressive Linear Precoder Design for Multiple Codewords MIMO ARQ Systems with ARQ Bundling Feedback

  • Zhang, Zhengyu;Qiu, Ling
    • Journal of Communications and Networks
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    • v.14 no.2
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    • pp.199-205
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    • 2012
  • This work investigates the progressive linear precoder design for packet retransmissions in multi-input multi-output (MIMO) systems with multiple codewords and automatic repeat request (ARQ) bundling feedback. Assuming perfect channel state information, a novel progressive linear ARQ precoder is proposed in the perspective of minimizing the packet error rate. We devise the ARQ precoder by combining power loading and sub channel pairing between current retransmission and previous transmissions. Furthermore, we extend the design to the case that the channel estimation error exists. Numerical results show that the proposed scheme can improve the performance of MIMO ARQ systems significantly regardless of the channel estimation error.

Estimation and Extraction of Unstable Frequency Lines of Acoustic Signal Using Neural Network

  • Ha, Seok-Wun;Hwang, Soo-Bok;Kim, Jae-Chang
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.2E
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    • pp.39-44
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    • 1999
  • In passive sonar, underwater moving objects are identified by the acoustic sounds they transmit. The spectrum of these sounds show features about the mechanism of the sound source, these features are discrete frequencies on the spectrum and frequency lines on the spectrogram. Variability in the underwater environment produce discontinuous broken or unstable fluctuating frequency lines. In this paper, we propose an efficient algorithm that estimate continuities of the discontinuous frequency lines and extract presence of the unstable frequency lines using neural networks and represent the proposed algorithm shows good performance in estimation and extraction the unstable frequency lines through the experiments.

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Evaluation for Fatigue Resistance of Small Wind Turbine Composite Blade according to GL Guideline (GL Guideline에 의거한 소형 풍력발전용 복합재 블레이드의 피로 저항성 평가)

  • Jang, Yun Jung;Kang, Ki Weon
    • The KSFM Journal of Fluid Machinery
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    • v.16 no.4
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    • pp.15-21
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    • 2013
  • This study aims to estimate the fatigue resistance of small wind composite blade using the fatigue life estimation formula in the GL guideline. For this, firstly, we estimated a turbine blade's bending moment spectrum by using wind profile wind profile and BEMT. And fatigue tests were performed to obtain the S-N curve of composite materials used in blade. In addition, a finite element analysis was used to identify fatigue critical locations and fatigue stress spectrum. And the fatigue resistance of composite blade were evaluated using the rainflow cycle counting, and Goodman diagram and the fatigue life estimation formula in the GL guideline.

A search-based high resolution frequency estimation providing improved convergence characteristics in power system (전력계통에서 수렴성 향상을 위한 탐색기반 고분해능 주파수 추정기법)

  • An, Gi-Sung;Seo, Young-Duk;Chang, Tae-Gyu;Kang, Sang-Hee
    • Journal of IKEEE
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    • v.22 no.4
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    • pp.999-1005
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    • 2018
  • This paper proposed a search-based high resolution frequency estimation method in power systme. The proposed frequency estimation method adopts a slope-based adaptive search as a base of adaptive estimation structure. The architectural and operational parameters in this adaptive algorithm are changed using the information from context layer analysis of the signals including a localized full-search of spectral peak. The convergence rate of the proposed algorithm becomes much faster than those of other conventional slope-based adaptive algorithms by effectively reducing search range with the application of the localized full-search of spectrum peak. The improvements in accuracy and convergence rate of the proposed algorithm are confirmed through the performance comparison with other representative frequency estimation methods, such as, DFT(discrete Fourier transform) method, ECKF(extended complex Kalman filter), and MV(minimum variable) method.