• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2006년도 International Symposium on GPS/GNSS Vol.1
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• pp.259-264
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• 2006

It is well known that the uncertainty of the covariance parameters of the process noise (Q) and the observation errors (R) has a significant impact on Kalman filtering performance. Q and R influence the weight that the filter applies between the existing process information and the latest measurements. Errors in any of them may result in the filter being suboptimal or even cause it to diverge. The conventional way of determining Q and R requires good a priori knowledge of the process noises and measurement errors, which normally comes from intensive empirical analysis. Many adaptive methods have been developed to overcome the conventional Kalman filter's limitations. Starting from covariance matching principles, an innovative adaptive process noise scaling algorithm has been proposed in this paper. Without artificial or empirical parameters to be set, the proposed adaptive mechanism drives the filter autonomously to the optimal mode. The proposed algorithm has been tested using road test data, showing significant improvements to filtering performance.

• 대한전자공학회논문지
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• 제21권4호
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• pp.7-12
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• 1984

DFT로 대각선화 할 수 있는 circulant matrix가 대칭이고 실수인 경우에 이를 대각선화 할 수 있는 CDFT(composite DFT)를 유도했다. 일반적인 실수 신호의 대칭 covariance matrix에 대하여 DFT와 CDFT 변환했을 경우의 variance 분포를 분석했고, 이를 토대로 rate distortion 이론에 의하여 이들의 성능을 비교한 결과 CDFT가 DFT보다 bit rate면에서 효과적임을 볼 수 있었다. 그리고 f(q)=(0.95)q인 covariance matrix(64×64)에 대해 CDFT가 DFT에 비해. 계산결과, 평균적으로 0.0095bit가 감소될 수 있었다.

• Journal of Welding and Joining
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• 제18권1호
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• pp.97-103
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• 2000

Time series analysis results show the SVD is a candidate of on-line monitoring of welding penetration when the covariance matrix of a full penetration is used as a mapping function. As the reconstructed embedding vectors from the chaotic scalar time series are manipulated by the covariance matrix, the mapped tim series lie on a hyper-ellipsoid which the lengths of semi-axes are the squared eigenvalues of the covariance matrix in the case of full penetration. These visualize by two dimensional stroboscope views. The other cases like partial penetration, are different in the sense of sizes and shapes. Here we test two types of time series; the ion current and the X-ray. The ion current is better than the X-ray as an on-line monitoring signal, because the difference of the eigenvalue spectrum of the ion(between the pull penetration and partial penetration) is bigger than those of the X-ray.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2003년도 학술회의 논문집 정보 및 제어부문 B
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• pp.449-451
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• 2003

The estimation of time-series data is fundamental process in many data analysis cases. However, the unwanted measurement error is usually added to true data, so that the exact estimation depends on efficient method to eliminate the error components. The wavelet transform method nowadays is expected to improve the accuracy of estimation, because it is able to decompose and analyze the data in various resolutions. Therefore, the wavelet based Kalman filter method for the estimation of time-series data is proposed in this paper. The wavelet transform separates the data in accordance with frequency bandwidth, and the detail wavelet coefficient reflects the stochastic process of error components. This property makes it possible to obtain the covariance of measurement error. We attempt the estimation of true data through recursive Kalman filtering algorithm with the obtained covariance value. The procedure is verified with the fundamental example of Brownian walk process.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1992년도 하계학술대회 논문집 A
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• pp.453-456
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• 1992

A Data-based Covariance Matrix(DCM) is introduced in the Eigenvector(EV) method, among subspace methods of estimating multiple sinusoidal frequencies from finite white noisy measurements. It is shown that the EV with the DCM can obtain the true. frequencies from finite noiseless data Some asymptotic results and further improvement on the DCM are also presented mathematically. Monte-carlo simulations are statistically conducted from the view-points of means and standard deviations in the EV's of DCM and Conventional Covariance Matrix(CCM). Simulations show a great promise for using the DCM, particularly for the cases of short data records, closely spaced frequencies and high signal-to-noise ratios.

• 대한전자공학회논문지
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• 제16권6호
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• pp.1-10
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• 1979

과학의 발달에 따라 원거리의, 그리고 더욱 접근하기 어려운 곳에서 일어나는 현상을 다루게 됨에 따라 약한 신호까지 취급하기를 원하게 되었다. 편재하고 있는 noise 속에 찾기 어려운 정도의 약한 신호를 다루게 됨에따라 random process를 취급할 줄 알아야 하게 되었고 금래 급격히 발달하고 있는 신호처리기술을 위해서는 이와 관련된 분야가 차지하는 상호위치를 파악하기가 어렵게 되었다. 신호처리의 입장에서 이러한 관련성과 본질의 재파악을 꾀하여 보았다. 이글은 우선 수학과 random 과정 분석의 기초에 한정되겠다.

• 한국음향학회:학술대회논문집
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• 한국음향학회 1993년도 학술논문발표회 논문집 제12권 1호
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• pp.206-209
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• 1993

The main purpose of this paper is to verify the effectiveness of a high resolution direction finding method, so called the‘averaged MUSIC’. This method uses a new sample array covariance matrix that consists of diagonal components obtained by taking averages of the diagonal component values of the sample covariance matrix for the MUSIC. The paper shows that the proposed method performs higher resolved direction-of-arrival estimation and better resolution probability than the MUSIC in such cases as low signal-to-noise ratio, when the number of sensors used is finite, based on the statistical analysis.

• 대한음성학회지:말소리
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• 제55권
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• pp.93-102
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• 2005

In this paper, sub-stream based eigenvoice method is proposed to overcome the weak points of conventional eigenvoice and dimensional eigenvoice. In the proposed method, sub-streams are automatically constructed by the statistical clustering analysis that uses the correlation information between dimensions. To obtain the reliable distance matrix from covariance matrix for dividing into optimal sub-streams, MAP adaptation technique is employed to the covariance matrix of training data and the sample covariance of adaptation data. According to our experiments, the proposed method shows $41\%$ error rate reduction when the number of adaptation data is 50.

• 한국통신학회논문지
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• 제12권5호
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• pp.428-438
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• 1987

本 論文은 大氣 空間에서 信號場과 雜音場을 處理하기 위하여 point-detector array檢波 시스템을 構成한 것이다. 또 variance 및 covariance Circuit도 구성했다. 이것들을 이용하여 測定한 直接檢波 最大出力은 理論値와 잘 一致함을 確認하였고 또한 實驗値는 joint-Gaussian理論曲線과 一致하였다.

• Journal of applied mathematics & informatics
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• 제27권5_6호
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• pp.1429-1433
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• 2009

The likelihood distance for the joint distribution of two multivariate normal distributions with common covariance matrix is explicitly derived. It is useful for identifying outliers which do not follow the joint multivariate normal distribution with common covariance matrix. The likelihood distance derived here is a good ground for the use of a generalized Wilks statistic in influence analysis of two multivariate normal data.