• International Journal of Control, Automation, and Systems
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• 제6권1호
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• pp.109-118
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• 2008

We present two estimators for discrete non-Gaussian and nonstationary probability density estimation based on a dynamic Bayesian network (DBN). The first estimator is for off line computation and consists of a DBN whose transition distribution is represented in terms of kernel functions. The estimator parameters are the weights and shifts of the kernel functions. The parameters are determined through a recursive learning algorithm using maximum likelihood (ML) estimation. The second estimator is a DBN whose parameters form the transition probabilities. We use an asymptotically convergent, recursive, on-line algorithm to update the parameters using observation data. The DBN calculates the state probabilities using the estimated parameters. We provide examples that demonstrate the usefulness and simplicity of the two proposed estimators.

• 대한수학회지
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• 제38권5호
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• pp.1061-1068
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• 2001

We write down explicity a recursive formula of one-pointed gravitational Gromov-Witten invariants and reduce the computation of them to a combinatoric problem which is not solved yet. The one-pointed invariants were played important role in Givental’s program in mirror symmetry. In section 3, we describe the combinatoric problem which can be read independently.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 추계학술대회 논문집 학회본부
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• pp.193-196
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• 1991

A method of extracting global, trend curves from input image that may locally not even contain small fragments of those curves using a hierarchical pyramid data structure is suggested. The smoothed input image is subsampled into a pyramid of lower-resolution versions by recursive computation of Gaussian-weighted sums. Trend curves are extracted by finding control points from ridges in these blurred images, and interpolating B-splines for those points.

• 대한전기학회논문지
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• 제39권4호
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• pp.380-385
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• 1990

This Paper presents a general algorithm for the parameter estimation of an antoregressive moving average process observed in additive white noise. The algorithm is based on the Gauss-Newton recursive prediction error method. For the parameter estimation, the output measurement is modelled as an innovation process using the spectral factorization, so that noise free RPE ARMA estimation can be used. Using apriori known properties leads to algorithm with smaller computation and better accuracy be the parsimony principle. Computer simulation examples show the effectiveness of the proposed algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2000년도 하계학술대회 논문집 A
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• pp.274-275
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• 2000

This paper introduces new ordering algorithms using the graph of data structure and forward/backward substitution of LU decomposition using recursive function. The performance of the algorithm is compared with Tinney's algorithm using 14 bus systems. Test results show that the new fill-in element of Jacobian matrix using the proposed ordering algorithm is same as that of Tinner scheme 3 and the forward/backward substitution can reduce the computation time

• 대한전기학회논문지
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• 제31권7호
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• pp.1-10
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• 1982

This paper derives the algorithm to estimate the operating cost, its marginal cost, and the reliability indices for the long term planning of power system. Treating the load duration curve and the system in the stochastic sense takes the place of the inverted load duration curve, effective load duration curve, and the numerical integration in the conventional methods. The time and accuracy of computation are substantially improved due to the fact that all expressions are represented by simple analytic form instead of the existing recursive form.

• 대한전자공학회논문지
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• 제24권4호
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• pp.667-674
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• 1987

In this paper an effective block matching algorithm is proposed to find the motion vector. There are two approaches to the estimation of the motion vector in MCC (motion compensated coding), i.e., pel(pixel element) recursive algorithm and block matching algorithm. The search algorithm in this paper is based on the block matching method. The advantage of a proposed algorithm using integral projections is the reduction of the computation time. While the conventional block matching methods have to be computed in 2-dimensional arrays, the proposed algorithm using integral projections can be computed in 1-dimensional arrays. In comparison with conventional block matching methods, a computer simulation shows that though the prediction error increases 0.23 db, it is not detectable for human eyes and the average reduction ratio of computation time obtained from the proposed algorithm is about 3-4.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 하계학술대회 논문집 B
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• pp.600-602
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• 1997

The kalman filter which has good estimating capabilities by means of the recursive computation from the previously known of obtained data is usually used for the system estimation in the case of not being directly measurable. The best estimating technique is still open issues on the PWR reactor control system to increase operating contingencies and to predict the safety margins for safer reactor operation. This paper addressed its estimating technique using kalman filter for the more flexible reactor control and showed the reasonable approach for discretization of the continuos-time system for reduction of computation errors.

• 대한전자공학회논문지
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• 제25권2호
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• pp.211-219
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• 1988

In this paper effective block matching algorithms are proposed to find the motion vector. There are two approaches to the estimation of the motion vector in MCC (motion compensated coding), i.e.pel(pixel element) recursive algorithm and block matching algorithm. The search algorithm in this paper is based on the block matching method. The advantage of this algorithm is the reduction of the computation time. In order to reduce the computation time, three mathods are proposed in this paper. These new algorithms are faster than other methods. Compared with the three step algorithm by Koga et al., the average ratio of the computational savings obtained from the proposed algorithm is about 3-4.

• ETRI Journal
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• 제43권6호
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• pp.1024-1037
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• 2021

Mining high utility itemsets (HUIs) from transaction databases considers such factors as the unit profit and quantity of purchased items. Two-phase tree-based algorithms transform a database into compressed tree structures and generate candidate patterns through a recursive pattern-growth procedure. This procedure requires a lot of memory and time to construct conditional pattern trees. To address this issue, this study employs two compressed tree structures, namely, Utility Count Tree and String Utility Tree, to enumerate valid patterns and thus promote fast utility computation. Furthermore, the study presents an algorithm called single-phase utility computation (SPUC) that leverages these two tree structures to mine HUIs in a single phase by incorporating novel pruning strategies. Experiments conducted on both real and synthetic datasets demonstrate the superior performance of SPUC compared with IHUP, UP-Growth, and UP-Growth+algorithms.