• Korean Journal of Computational Design and Engineering
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• v.10 no.5
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• pp.314-327
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• 2005

This paper describes the volumetric data modeling and analysis methods that employ volumetric NURBS or VNURBS that represents heterogeneous objects or fields in multidimensional space. For volumetric data modeling, we formulate the construction algorithms involving the scattered data approximation and the curvilinear grid data interpolation. And then the computational algorithms are presented for the geometric and mathematical analysis of the volume data set with the VNURBS model. Finally, we apply the modeling and analysis methods to various field applications including grid generation, flow visualization, implicit surface modeling, and image morphing. Those application examples verify the usefulness and extensibility of our VNUBRS representation in the context of volume modeling and analysis.

• Korean Journal of English Language and Linguistics
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• v.4 no.2
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• pp.175-194
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• 2004

This paper provides computational algorithms for English Questions, by which we can effectively handle and implement Yes-No Questions and Wh-Questions. Those algorithms will be developed in Categorial Grammar. In this paper, we will modify and revise Steedman＇s Combinatory Categorial Grammar (CCG) so that we can computationally implement Questions effectively, which will be called a CCG-like system. In this system, semantic interpretations of Questions will be calculated compositionally based on the functor-arguments relations of the constituents. In sum, this paper provides analyses of Questions in Categorial Grammar, by which we can effectively implement Questions in English.

• Journal of applied mathematics & informatics
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• v.4 no.2
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• pp.407-418
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• 1997

In this paper we establish the equivalence between the general resolvent equations and variational inequalities. This equiva-lence is used to suggest and analyze a number of iterative algorithms for solving variational inclusions. We also study the convergence criteria of the iterative algorithms. Our results include several pre-viously known results as special cases.

• Journal of applied mathematics & informatics
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• v.34 no.1_2
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• pp.61-73
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• 2016

In this paper, we consider the problems of convergence of parallel iterative algorithms for a system of nonlinear variational inequalities and nonexpansive mappings. Strong convergence theorems are established in the frame work of real Banach spaces.

• Journal of applied mathematics & informatics
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• v.5 no.3
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• pp.691-700
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• 1998

Simulation algorithms for one-sided and two-sided trun-cated gamma distributions are proposed. These algorithms suggest the optimal choice of derived functions. Some results of simulation are given. Finally an application with real data is presented.

• Journal of Korean Institute of Industrial Engineers
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• v.18 no.1
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• pp.177-184
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• 1992

The control policy algorithm is examined and compared in this study. This research investigates a two state partially observable Markov chain in which only deterioration can occur and for which the only actions possible are to replace or to live alone. The goal of this research is to compare the computational efficiencies of control policy algorithm. One is Sondik's algorithms and the other one is jump algorithm.

• IEMEK Journal of Embedded Systems and Applications
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• v.13 no.1
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• pp.1-8
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• 2018

This paper proposes a low complexity super resolution algorithm for frequency modulated continuous wave (FMCW) radar systems for foreign object debris (FOD) detection. FOD radar has a requirement to detect foreign object in small units in a large area. However, The fast Fourier transform (FFT) method, which is most widely used in FMCW radar, has a disadvantage in that it can not distinguish between adjacent targets. Super resolution algorithms have a significantly higher resolution compared with the detection algorithm based on FFT. However, in the case of the large number of samples, the computational complexity of the super resolution algorithms is drastically high and thus super resolution algorithms are difficult to apply to real time systems. In order to overcome this disadvantage of super resolution algorithm, first, the proposed algorithm coarsely obtains the frequency of the beat signal by employing FFT. Instead of using all the samples of the beat signal, the number of samples is adjusted according to the frequency of the beat signal. By doing so, the proposed algorithm significantly reduces the computational complexity of multiple signal classifier (MUSIC) algorithm. Simulation results show that the proposed method achieves accurate location even though it has considerably lower complexity than the conventional super resolution algorithms.

• The Journal of the Acoustical Society of Korea
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• v.20 no.1
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• pp.43-49
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• 2001

EVRC (Enhanced Variable Rate Codec) has been adopted as a standard coder for the CDMA digital cellular system in North America and Korea, and known to provide good call quality at 8kbps. In this paper, fast implementation algorithms for EVRC encoder are proposed. The proposed algorithms are based on both efficient pitch detection scheme and fast fixed codebook search algorithm. In the codebook search, computational complexity is reduced down to 70％ of the original EVRC by limiting the number of pulse position combination and by using a truncated impulse response. The proposed algorithms enable us to implement the EVRC with much smaller computational works. Also, informal subjective tests confirmed that the difference in the speech quality between the original EVRC and the proposed method was indistinguishable.

• Journal of Broadcast Engineering
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• v.9 no.4 s.25
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• pp.384-390
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• 2004

In this paper we compare the performance of 4 different algorithms for converting the sampling frequency of an audio from 44.1KHz to 48KHz. The algorithms considered here include the basic polyphase method. sine function based method. multi-stage method. and B-spline based method. For a fair comparison, the sampling rate converters using the 4 algorithms are redesigned under a high fidelity condition. Then, their H/W complexities are compared in terms of the computational complexity and the memory size. As a result, it is shown that the basic polyphase method and sine function based method outperform the other two in terms of the computational complexity, while the B-spline based method requires less memory than the others.

• Journal of the Institute of Convergence Signal Processing
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• v.12 no.2
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• pp.128-132
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• 2011

Least mean square adaptive algorithms have played important role in radar, sonar, speech processing, and mobile communication. In mobile communication area, the convergence rate of a LMS algorithm is quite important. However, LMS algorithms have slow and non-uniform convergence rate problem For overcoming these shortcomings, various variable step LMS adaptive algorithms have been studied in recent years. Most of these recent LMS algorithms have used complex variable step methods to get a rapid convergence. But complex variable step methods need a high computational complexity. Therefore, the main merits such as the simplicity and the robustness in a LMS algorithm can be eroded. The proposed deterministic variable step LMS algorithm is based upon a simple deterministic function for the step update so that the simplicity of the proposed algorithm is obtained and the fast convergence is still maintainable.