• The Journal of the Acoustical Society of Korea
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• v.16 no.2E
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• pp.38-46
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• 1997

The objective of the paper is to compare the computational complexity of five algorithms for computing time-domain second-order Volterra filter outputs in terms of number of real multiplication and addition operations required for implementation. This study shows that if the filter memory length is greater that or equal to 16, the fast algorithm using the overlap-save method and the frequency-domain symmetry properties of the quadratic coefficients is the most efficient among the algorithms investigated in this paper, When the filter memory length is less than 16, the algorithm using the time-domain symmetry properties is better than any other algorithm.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.813-820
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• 2018

This paper proposes new frame rate up-conversion algorithms. Adaptive motion estimation based on block complexity information are used to obtain more accurate motion vectors. Because the information on block complexity is extracted from the motion estimation prediction size from the original frame, additional computational complexity is not imparted. In experimental results, the proposed algorithms provide robust frame interpolation performance for whole test sequences. Also, the computational complexity of the proposed algorithm is reduced to a benchmark algorithm.

• Transactions of the Korean Society of Automotive Engineers
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• v.19 no.4
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• pp.84-90
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• 2011

In active noise control filter, LMS algorithms which used for control filter, assure the convergence property, and computational burden of these algorithms are proportionate to the filter taps. The convergence speed of LMS algorithms is mainly determined by value of the convergence coefficient, so optimal selection of the value of convergence coefficient is very important. In this paper, We proposed novel adaptive fuzzy logic LMS algorithms with FIR filter structure which has better convergence speed and less computational burden than conventional LMS algorithms, for single channel active noise control with ill conditioned signal case. Computer simulations were performed to show the effectiveness of a proposed algorithms.

• Journal of IKEEE
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• v.6 no.2 s.11
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• pp.111-118
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• 2002

In this paper, we present a variable block method to reduce additive computational requirements in determining step-size of variable step-size LMS (VS-LMS) algorithms. The block length is inversely proportional to the changing of step-size in VS-LMS algorithm. The technique reduces computational requirements of the conventional VS-LMS algorithms without a degradation of performance in convergence rate and steady state error. And a method for deriving initial step-size, when the input is zero mean, white Gaussian sequence, is proposed. For demonstrating the good performances of the proposed method, simulation results are compared with the conventional variable step-size algorithms in convergence speed and computational requirements.

• Journal of applied mathematics & informatics
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• v.12 no.1_2
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• pp.375-384
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• 2003

We introduce some algorithms for computing Mathematics and also give some questions based on the results from computations using CoCoA and Splus.

• Journal of Multimedia Information System
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• v.8 no.3
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• pp.191-196
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• 2021

Computational thinking refers to the process and method of solving everyday problems using computers. When teaching a computational thinking class for computer majors and non-majors at university, the easiest example to deliver the concept of computational thinking is sorting. Sorting is the concept of arranging given data in order. In this work, we have implemented four visualized sorting algorithms that anyone can easily use. In particular, it helps to understand the difference between the algorithms by showing the number of comparisons and exchanges between elements, which are the criteria for evaluating the performance of the sorting algorithm in real time. It was confirmed that the practice of using the sorting visualization app developed in this research contributed to the improvement of students' understanding of computational thinking.

• Journal of applied mathematics & informatics
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• v.7 no.2
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• pp.439-451
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• 2000

To compute derivatives using matrix vector multiplication method, new algorithms were introduced in [1.2]n By these algorithms, we reduced roundoff error in computing derivative using Chebyshev collocation methods (CCM). In this paper, some applications of these algorithms ar presented.

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.393-404
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• 2004

We introduce several algorithms for adding up Artinian O-sequences to obtain the maximal possible Betti numbers among all minimal free resolutions with the given Hilbert function. Moreover, we give open questions based on the outputs using those algorithms.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2006.04a
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• pp.535-540
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• 2006

Recently, the resizing algorithms based on the displacement participation factors have been developed for sizing members to satisfy stiffness criteria. It is proved that this resizing algorithms made for utilizing worker's stiffness design are practical and rational when applied to aseismatic design in the range of elastic until now. However, by the preceding research we confirmed that the inelastic performance of steel moment-resisting frame designed by resizing algorithms is not better than that of the frame before resizing. We present therefore a plan for improving inelastic performance of steel moment-resizing frame to which resizing algorithms applied in this paper.

• Journal of applied mathematics & informatics
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• v.15 no.1_2
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• pp.53-75
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• 2004

First, we present two classes of sequential algorithms for minimum flow problem: decreasing path algorithms and preflow algorithms. Then we describe another approach of the minimum flow problem, that consists of applying any maximum flow algorithm in a modified network. In section 5 we present several parallel preflow algorithms that solve the minimum flow problem. Finally, we present an application of the minimum flow problem.