• Title/Summary/Keyword: Spectral Estimation

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A Study on Vibration Transfer Path Identification of Vehicle Driver's Position by Multi-dimensional Spectral Analysis (다차원 스펙트럼 해석법을 이용한 차실내 운전자석 진동전달경로 규명에 관한 연구)

  • Lee, You-Yub;Park, Sang-Gil;Oh, Jae-Eung
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.17 no.8
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    • pp.741-746
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    • 2007
  • In this study, transfer path identification and output estimation are simulated by multi-dimension spectral analysis method (MDSA). Multi -input/single-output system give expression the vehicle suspension which each inputs are correlated reciprocally. In case of correlating with inputs, the system needs separating the each input signal by MDSA. Main simulations are about finding effective input by coherent output spectrum and selecting optimal input's number by multiple coherence function. Also, by shielding transfer path of each input, transfer path characteristic is identified in terms of overall integrated contribution level.

URBAN COMPLEXITY ESTIMATION INDICES BASED ON 3D DISCRETE WAVELET TRANSFORM OF REMOTELY SENSED IMAGERY;THE PRELIMINARY INTERPRETATION WITH LAND COVER MAP

  • Yoo, Hee-Young;Lee, Ki-Won;Kwon, Byung-Doo
    • Proceedings of the KSRS Conference
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    • 2007.10a
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    • pp.405-409
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    • 2007
  • Each class in remotely sensed imagery has different spectral and spatial characteristics. Natural features have relatively smaller spatial changes than spectral changes. Meanwhile, urban area in which buildings, roads, and cars are included is inclined to face more changes of spatial variation than spectral one. This study aims to propose the new urban complexity index (UCI) based on the 3D DWT computation of remotely sensed imageries considering these characteristics. And then we analyze relation between index and land cover map. The 3DWUCI values are related to class and the indices of urban area are greater than natural area. The proposed UCI could be used to express effectively the standard of urban complexity over a wide area.

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Korean Seismic Station Site Effect Estimation Using Generalized Inversion Technique (일반 역산 기법을 활용한 한국 지표 관측소 부지 효과 평가)

  • Jee, Hyun Woo;Han, Sang Whan
    • Journal of the Earthquake Engineering Society of Korea
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    • v.27 no.2
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    • pp.111-118
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    • 2023
  • The 2017 Pohang earthquake afflicted more significant economic losses than the 2016 Gyeongju earthquake, even if these earthquakes had a similar moment magnitude. This phenomenon could be due to local site conditions that amplify ground motions. Local site effects could be estimated from methods using the horizontal-to-vertical spectral ratio, standard spectral ratio, and the generalized inversion technique. Since the generalized inversion method could estimate the site effect effectively, this study modeled the site effects in the Korean peninsula using the generalized inversion technique and the Fourier amplitude spectrum of ground motions. To validate the method, the site effects estimated for seismic stations were tested using recorded ground motions, and a ground motion prediction equation was developed without considering site effects.

A Study on the Estimation Method of Automative Ride Comfort (자동차 승차감 평가 방법에 관한 연구)

  • 황성연
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 1997.10a
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    • pp.108-113
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    • 1997
  • In these days, customers require high-quality, high-performance, high-ride comfort for Automobile and then the automotive manufacturers concentrated on study of electrical, high-performance, low-cost of parts and sub-parts. In this paper, for ride comfort estimation PSD(Power Spectral Density) of acceleration at eight test point are measured, and then are calculated with new index of ride comfort. The new index of ride comfort developed for optimal design, real test, applied the actual. It can apply for various fields.

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Spectral analysis of random process

  • Akizuki, Kageo
    • 제어로봇시스템학회:학술대회논문집
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    • 1994.10a
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    • pp.13-20
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    • 1994
  • The spectrum estimation methods of random processes are expressed in this paper. Beginning with the basic theory, non-parametric and parametric methods are overviewed. As to non-parametric method, numerical calculation method is also discussed. As to parametric method, AR model is a very famous and effective model representing random process. Estimation methods of AR parameters which have been proposed are mentioned here. Wavelet analysis is a recently interested technique in signal processing. An application of wavelet analysis is also shown.

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A study on the parameter estimate using selective recursive least square (SRLS을 이용한 파라미터 추정에 관한 연구)

  • 유치형;이재하;정찬수
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.441-444
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    • 1989
  • This correspondence presents a recursive estimation algorithm which, unlike conventional ones; updates the estimates only when a sufficient improvement can be obtained with a bounded noise assumption, the resulting sequence of estimates is a sequence of convex sets(ellipsoids) in the parameter space. For the cases studied, the algorithm use less than 20 percent of the. data to update, the estimate and still acquired good accuracy for spectral estimation.

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Study of Spectral Reflectance Reconstruction Based on an Algorithm for Improved Orthogonal Matching Pursuit

  • Leihong, Zhang;Dong, Liang;Dawei, Zhang;Xiumin, Gao;Xiuhua, Ma
    • Journal of the Optical Society of Korea
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    • v.20 no.4
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    • pp.515-523
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    • 2016
  • Spectral reflectance is sparse in space, and while the traditional spectral-reconstruction algorithm does not make full use of this characteristic sparseness, the compressive sensing algorithm can make full use of it. In this paper, on the basis of analyzing compressive sensing based on the orthogonal matching pursuit algorithm, a new algorithm based on the Dice matching criterion is proposed. The Dice similarity coefficient is introduced, to calculate the correlation coefficient of the atoms and the residual error, and is used to select the atoms from a library. The accuracy of Spectral reconstruction based on the pseudo-inverse method, Wiener estimation method, OMP algorithm, and DOMP algorithm is compared by simulation on the MATLAB platform and experimental testing. The result is that spectral-reconstruction accuracy based on the DOMP algorithm is higher than for the other three methods. The root-mean-square error and color difference decreases with an increasing number of principal components. The reconstruction error decreases as the number of iterations increases. Spectral reconstruction based on the DOMP algorithm can improve the accuracy of color-information replication effectively, and high-accuracy color-information reproduction can be realized.

The Power Spectral Estimation of Heart Rate Variability using Lomb-Scargle's algorithm (Lomb-Scargle알고리즘에 의한 심박변동의 파워스펙트럼 추정)

  • Shin, K.S.;Jeong, K.S.;Choi, S.J.;Lee, J.W.;Lee, M.H.
    • Proceedings of the KOSOMBE Conference
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    • v.1997 no.05
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    • pp.275-278
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    • 1997
  • Standard methods estimating the power spectral density(PSD) from an irregularly sampled cardiac event series require deriving a new evenly-spaced signal applicable to those methods. To avoid that requirement, in this study, the power spectrum of heart rate variability was estimated by Lomb-Scargle's algorithm, which is a means of obtaining PSD estimates directly from irregularly sampled timeseries observed in astronomy. To assess the performance of Lomb-Scargle algorithm in the power spectral analysis of heart rate variability, it was applied to various cardiac event series derived through integral pulse frequency modulation model(IPFM) simulation and from real ECG signals, and the resultant power spectra was compared with those obtained by a conventional method based on the FFT. In result, it is concluded that Lomb-Scargle's periodogram is very effective in the power spectral analysis of heart rate variability, especially in the presence of arrhythmia and/or dropouts of cardiac events.

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An efficient Video Dehazing Algorithm Based on Spectral Clustering

  • Zhao, Fan;Yao, Zao;Song, Xiaofang;Yao, Yi
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.7
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    • pp.3239-3267
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    • 2018
  • Image and video dehazing is a popular topic in the field of computer vision and digital image processing. A fast, optimized dehazing algorithm was recently proposed that enhances contrast and reduces flickering artifacts in a dehazed video sequence by minimizing a cost function that makes transmission values spatially and temporally coherent. However, its fixed-size block partitioning leads to block effects. The temporal cost function also suffers from the temporal non-coherence of newly appearing objects in a scene. Further, the weak edges in a hazy image are not addressed. Hence, a video dehazing algorithm based on well designed spectral clustering is proposed. To avoid block artifacts, the spectral clustering is customized to segment static scenes to ensure the same target has the same transmission value. Assuming that edge images dehazed with optimized transmission values have richer detail than before restoration, an edge intensity function is added to the spatial consistency cost model. Atmospheric light is estimated using a modified quadtree search. Different temporal transmission models are established for newly appearing objects, static backgrounds, and moving objects. The experimental results demonstrate that the new method provides higher dehazing quality and lower time complexity than the previous technique.

Implementation of a Robust Speech Recognizer in Noisy Car Environment Using a DSP (DSP를 이용한 자동차 소음에 강인한 음성인식기 구현)

  • Chung, Ik-Joo
    • Speech Sciences
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    • v.15 no.2
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    • pp.67-77
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    • 2008
  • In this paper, we implemented a robust speech recognizer using the TMS320VC33 DSP. For this implementation, we had built speech and noise database suitable for the recognizer using spectral subtraction method for noise removal. The recognizer has an explicit structure in aspect that a speech signal is enhanced through spectral subtraction before endpoints detection and feature extraction. This helps make the operation of the recognizer clear and build HMM models which give minimum model-mismatch. Since the recognizer was developed for the purpose of controlling car facilities and voice dialing, it has two recognition engines, speaker independent one for controlling car facilities and speaker dependent one for voice dialing. We adopted a conventional DTW algorithm for the latter and a continuous HMM for the former. Though various off-line recognition test, we made a selection of optimal conditions of several recognition parameters for a resource-limited embedded recognizer, which led to HMM models of the three mixtures per state. The car noise added speech database is enhanced using spectral subtraction before HMM parameter estimation for reducing model-mismatch caused by nonlinear distortion from spectral subtraction. The hardware module developed includes a microcontroller for host interface which processes the protocol between the DSP and a host.

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