• Title/Summary/Keyword: correlation algorithm

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A Method for Selecting Ground Motions Considering Target Response Spectrum Mean, Variance and Correlation - I Algorithm (응답 스펙트럼의 평균과 분산, 상관관계를 모두 고려한 지반운동 선정 방법 - I 알고리즘)

  • Han, Sang Whan;Ha, Seong Jin;Cho, Sun Wook
    • Journal of the Earthquake Engineering Society of Korea
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    • v.20 no.1
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    • pp.55-62
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    • 2016
  • It is important to select an accurate set of ground motions when conducting linear and nonlinear response history analyses of structures. This study proposes a method for selecting ground motions from a ground motion library with response spectra that match the target response spectrum mean, variance and correlation structures. This study also has addressed the determination of an appropriate value for the weight factor of a correlation structure. The proposed method is conceptually simple and straightforward, and does not involve a simulation algorithm. In this method, a desired number of ground motions are sequentially selected from first to last. The proposed method can be also used for selecting ground motions with response spectra that match the conditional spectrum. The accuracy and efficiency of the proposed procedure are verified with numerical examples.

Development of Fast and Exact FFT Algorithm for Cross-Correlation PIV (상호상관 PIV기법을 위한 빠르고 정확한 FFT 알고리듬의 개발)

  • Yu, Kwon-Kyu;Kim, Dong-Su;Yoon, Byung-Man
    • Journal of Korea Water Resources Association
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    • v.38 no.10 s.159
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    • pp.851-859
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    • 2005
  • Normalized cross-correlation (correlation coefficient) is a useful measure for pattern matching in PIV (Particle Image Velocimetry) analysis. Because it does not have a corresponding simple expression in frequency domain, several fast but inexact measures have been used. Among them, three measures of correlation for PIV analysis and the normalized cross-correlation were evaluated with a sample calculation. The test revealed that all other proposed correlation measures sometimes show inaccurate results, except the normalized cross-correlation. However, correlation coefficient method has a weakpoint that it requires so long time for calculation. To overcome this shortcoming, a fast and exact method for calculating normalized cross-correlation is suggested. It adopts Fast Fourier Transform (FFT) for calculation of covariance and the successive-summing method for the denominator of correlation coefficient. The new algorithm showed that it is really fast and exact in calculating correlation coefficient.

Family of Cascade-correlation Learning Algorithm (캐스케이드-상관 학습 알고리즘의 패밀리)

  • Choi Myeong-Bok;Lee Sang-Un
    • Journal of the Korean Institute of Intelligent Systems
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    • v.15 no.1
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    • pp.87-91
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    • 2005
  • The cascade-correlation (CC) learning algorithm of Fahlman and Lebiere is one of the most influential constructive algorithm in a neural network. Cascading the hidden neurons results in a network that can represent very strong nonlinearities. Although this power is in principle useful, it can be a disadvantage if such strong nonlinearity is not required to solve the problem. 3 models are presented and compared empirically. All of them are based on valiants of the cascade architecture and output neurons weights training of the CC algorithm. Empirical results indicate the followings: (1) In the pattern classification, the model that train only new hidden neuron to output layer connection weights shows the best predictive ability; (2) In the function approximation, the model that removed input-output connection and used sigmoid-linear activation function is better predictability than CasCor algorithm.

A Study on Correlation Interference Signal Cancellation Algorithm for Target Estimation in Multi Input Multi Output (다중 입력 다중 출력 배열 시스템에서 목표물 추정을 위한 상관성 간섭신호 제거 알고리즘 연구)

  • Lee, Kwan-Hyeong;Song, Woo-Young;Lee, Myeong-Ho
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.13 no.1
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    • pp.89-93
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    • 2013
  • This paper is estimating a target direction of arrival with incident to receiver in spatial. This paper presented covariance using constraint matrix to correlation interference signal cancellation in multi input multi output array antennas system. we proposed a target direction of arrival estimation algorithm using cost function and minimum variance method. Through simulation, we were analysis a performance to compare general SPT-LCMV algorithm and proposal algorithm. We showed that proposal algorithm improve more target estimation than general SPT-LCMV algorithm in direction of arrival.

Fast and Accurate Algorithm for Motion Estimation in Mobile Environments (모바일 환경에서 모션 추정을 위한 빠르고 정확한 알고리즘)

  • Kim, Jun-Ho;Oh, Il-Seok
    • The Journal of the Korea Contents Association
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    • v.10 no.3
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    • pp.1-9
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    • 2010
  • In this paper, we propose a new method of improving accuracy of motion estimation in mobile environments, compared with Rosten's algorithm. The present method selects corners as feature points. The Rosten's algorithm uses simple addition and subtraction to detect the corners. Although it has the advantage of faster processing speed, Rosten's algorithm has a drawback of low performance in motion estimation. We use the NCC(Normalized Cross Correlation) coefficients to match the corners, and remove in two steps the outliers of inaccurate matching corners. We compare the proposed algorithm with Rosten's algorithm by applying both to the real images. We find that the proposed method shows better performance than Rosten's algorithm in motion estimation. In addition, we implement the present method on mobile devices and confirm that it works in mobile environments in real time.

Image Based Damage Detection Method for Composite Panel With Guided Elastic Wave Technique Part II. Damage Size Estimation Algorithm (복합재 패널에서 유도 탄성파를 이용한 이미지 기반 손상탐지 기법 개발 Part II. 손상크기 추정 알고리즘)

  • Kim, Changsik;Jeon, Yongun;Park, Jungsun;Cho, Jin Yeon
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.49 no.1
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    • pp.13-20
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    • 2021
  • In this paper, a new algorithm is proposed to estimate the damage size by combining the reflected area with the reflected position and extracting contours in proportion to the maximum value of pixels from the visible image. The cumulative summation feature vector algorithm is used to obtain the area of the reflected signal. To get the position of the reflected signal, the signal correlation algorithm is used to decompose the reflected signal from the damage. The proposed algorithm is tested and validated for composite panels. Repetitive experiments are performed and it is confirm that the proposed algorithm is reproducible. Further, it is verified that the damage size can be estimated appropriately by the proposed algorithm.

Characteristics of Filtered-X LMS Algorith for Two Tone Noise (두 정현파 소음에 대한 Filtered-X LMS 알고리즘의 특성연구)

  • 김현석;박영진
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 1994.04a
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    • pp.16-21
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    • 1994
  • For the systems such as ANC(Active Noise Control) systems having auxiliary path after FIR type adaptive filter, Filtered-X LMS algorithm is effective. However behaviors of this algorithm has not been fully understood. The convergence property of this algorithm depends on not only cross correlation matrix between the filtered signals through model and real auxiliary path state solution of weight vector in Filtered-X LMS algorithm is investigated for under-determined case, over-determined case, and nonsingular case. Also, the convergence speed in case of two tone noise is investigated based on the eigenvalue spread of cross correlation matrix.

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Locating Chest Boundary in Sequential Images by Snakes (Snakes를 이용한 흉부 연속영상의 외부윤곽검출)

  • Hwang, Y.H.;Choi, W.Y.
    • Proceedings of the KOSOMBE Conference
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    • v.1997 no.11
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    • pp.236-239
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    • 1997
  • Snakes is an active contour model or representing image contours. To detect chest boundary on thoracic MRI sequences, we proposed a method based on modified greedy algorithm. Because thoracic MRI sequences have a spatial correlation, we added energy term related with spatial correlation to Snakes energy formulation. A measure of shape similarity called the BMD was used to evaluate the accuracy of the algorithm. The average BMD value or the modified algorithm's result is higher than greedy algorithm's.

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Probabilistic Target Speech Detection and Its Application to Multi-Input-Based Speech Enhancement (확률적 목표 음성 검출을 통한 다채널 입력 기반 음성개선)

  • Lee, Young-Jae;Kim, Su-Hwan;Han, Seung-Ho;Han, Min-Soo;Kim, Young-Il;Jeong, Sang-Bae
    • Phonetics and Speech Sciences
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    • v.1 no.3
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    • pp.95-102
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    • 2009
  • In this paper, an efficient target speech detection algorithm is proposed for the performance improvement of multi-input speech enhancement. Using the normalized cross correlation value between two selected channels, the proposed algorithm estimates the probabilistic distribution function of the value from the pure noise interval. Then, log-likelihoods are calculated with the function and the normalized cross correlation value to detect the target speech interval precisely. The detection results are applied to the generalized sidelobe canceller-based algorithm. Experimental results show that the proposed algorithm significantly improves the speech recognition performance and the signal-to-noise ratios.

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A Polynomial Complexity Optimal Multiuser Detection Algorithm Based on Monotonicity Properties

  • Quan, Qingyi
    • ETRI Journal
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    • v.32 no.3
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    • pp.479-481
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    • 2010
  • An optimal multiuser detection algorithm with a computational complexity of O(K log K) is proposed for the class of linear multiple-access systems which have constant cross-correlation values. Here the optimal multiuser detection is implemented by searching for a monotone sequence with maximum likelihood, under the ranking of sufficient statistics. The proposed algorithm is intuitive and concise. It is carried out in just two steps, and at each step only one kind of operation is performed. Also, the proposed algorithm can be extended to more complex systems having more than a single cross-correlation value.