• 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.

• The Journal of Engineering Geology
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• v.25 no.1
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• pp.103-113
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• 2015

This study presents a novel algorithm for determining the P-wave arrival time using amoving window function to improve source localization in low-SNR (signal-to-noise ratio)acoustic emissions. The proposed algorithm was applied to low-SNR signals to verify the accuracy of measurements against existing algorithms. When other algorithms were applied, the test results revealed that SNR decreased and accuracy was reduced, especially where SNR wasless than 2.14. The proposed algorithm using amoving window function considers the frequency characteristic and signal amplitude simultaneously, and produced reliable results where SNR was 2.14.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2005.11a
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• pp.317-320
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• 2005

기존의 블라인드 등화(blind equalization) 알고리즘의 step-size는 임의의 값을 알고리즘에 적용하여 수렴속도와 정상 상태의 특성을 고려하여 최적한 step-size를 결정하였다. step-size를 크게 하면 수렴속도는 빠른 반면에 정상 상태에서 에러가 크고, step-size를 작게 하면 수렴속도는 느린 반면에 정상 상태에서 에러가 작아진다. 그렇기 때문에 수렴속도와 정상 상태를 고려해서 step-size를 결정해야 되고, 특별하게 정해지는 기준이 없기 때문에 연구자의 판단에 의해서 다르게 선택된다. 본 논문에서는 등화기 출력의 잔류 심벌간 간섭에 따라 step-size를 가변함으로서 수렴속도 및 정상 상태 성능을 개선한 가변 step-size를 갖는 블라인드 등화 알고리즘을 제안한다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.8 no.12
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• pp.89-95
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• 1985

MRP System에서 시스템 성능을 향상시킬 수 있는 하나의 인자는 우수한 Lot-Sizing rule의 선택과 발견이다. 널리 사용되고 있는 Lot-Sizing rule 들 중 Wagner-Whitin 알고리즘은 생산준비 비용과 재고 유지비용이 가변적일 경우 동적 로트크기 결정에 우수한 forward 알고리즘이다. 본 연구에서는 Wagner-Whitin 알고리즘의 중요 원리들을 응용하여 LDS 알고리즘이라 명명한 backward 알고리즘을 개발한다. 그리고 개발된 알고리즘을 Wagner-Whitin 알고리즘과 비교함으로 그 유효성을 테스트하고 backward 알고리즘이 가지는 계산상의 장점을 고찰한다.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.141-144
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• 2003

가장 최근의 동영상 압축 표준인 H.264는 매크로블록의 최적 모드를 결정하기 위하여 총 7가지 모드를 사용하여 움직임 예측을 수행하기 때문에 부호화 효율과 수행 성능 면에서 기존의 방식에 비해 좋은 결과를 보이지만, 움직임 예측 과정에서 많은 계산 시간을 필요로 한다는 것이 커다란 단점으로 지적되고 있다. 따라서, 본 논문에서는 H.264에서 가변 블륵 단위의 움직임 예측 시 인접한 블록과의 상관성을 분석하여 다음 움직임 예측 모드의 사용 여부를 결정하는 블록 병합 알고리즘을 HEXBS(Hexagon-based Search) 고속 움직임 탐색 알고리즘에 적용하여 움직임 예측 시간을 효율적으로 절약하는 방법을 제안한다.

• Journal of the Korea Society for Simulation
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• v.26 no.4
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• pp.1-9
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• 2017

The Genetic Algorithm(GA) is a global search algorithm based on biological genetics. It is widely used in various fields such as industrial applications, artificial neural networks, web applications and defense industry. However, conventional Genetic Algorithm has difficulty maintaining feasibility in complicated situations due to its fixed number of chromosomes. This study proposes the Genetic Algorithm using variable chromosome with chromosome attachment. And in order to verify the implication of changing number of chromosomes in the simulation, it applies the Genetic Algorithm using variable chromosome with chromosome attachment to antisubmarine High Value Unit(HVU) escort mission simulation. As a result, the Genetic Algorithm using variable chromosome has produced complex strategies faster than the conventional method, indicating the increase of the number of chromosome during the process.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.3
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• pp.77-82
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• 2018

This paper is concerned with the performance analysis of a modified stop-and-go generalized multi-modulus algorithm (MSAG-GMMA) adaptive blind equalization algorithm with variable step size. The proposed algorithm multiplies the fixed step size by the error signal of the decision-oriented algorithm in the equalization coefficient update equation, and changes the step size according to the error size. Also, the MSAG-GMMA having a fixed step size is operated so as to maintain a fast convergence speed from a certain threshold to a steady state by determining the error signal size of the decision-directed algorithm, and when the MSAG-GMMA to work To evaluate the performance of the proposed algorithm, we use the ensemble ISI, ensemble-averaged MSE, and equalized constellation obtained from the output of the equalizer as the performance index. Simulation results show that the proposed algorithm has faster convergence speeds than MMA, GMMA, and MSAG-GMMA and has a small residual error in steady state.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.20 no.3
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• pp.53-58
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• 2020

This paper is concerned with the performance analysis of MSAGF-MMA with variable step size whose step size varies according to input power signal and decision-directed error signal. The proposed algorithm is made to change according to the input power signal which can reliably increase the convergence speed to the steady state by making the step size less affected by the fluctuation of the input signal in the MMA having the binary flag obtained from the modified Stop-and-Go algorithm. At the same time, the step size can be varied according to the decision-directed error signal so that the residual error can be reduced in the steady state. As a result of computer simulations, it is confirmed that the proposed algorithm has a very good performance in the evaluation of residual ISI and averaged-MSE in steady state as well as in terms of convergence speed to steady state compared to MMA and MSAGF-MMA.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.3
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• pp.89-95
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• 2016

In this paper, we propose a dual-mode blind equalization algorithm that two of the blind equalization algorithm using the size of the decision-directed error signal is automatically switched. The proposed algorithm has a faster convergence speed due to operation of the MSAGF-SMMA with large fixed step-size mainly in the initial equalization. After the equalization has been made to some extent, the proposed algorithm has a smaller residual error in the steady- state by operation of the MSAGF-SMMA with a variable step-size mainly. The variable step-size is determined by multiplying the size of the decision-directed error signal of a fixed step-size. In this paper, we analyze the performance of the proposed algorithm. The computer simulation results demonstrate that the proposed algorithm has a significantly improved performance in terms of a residual inter-symbol interference and residual error in the steady-state compared with the MMA, SMMA, and MSAGF-SMMA.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.5
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• pp.111-116
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• 2004

It is essential to know the information about the prior model for wavelet coefficients, the probability distribution of noise, and the variance of wavelet coefficients for noise reduction using Bayesian estimation in wavelet domain. In general denoising methods, the signal variance is estimated from the proper prior model for wavelet coefficients. In this paper, we propose a variable window size decision algorithm to estimate signal variance according to image region. Simulation results shows the proposed method have better PSNRs than those of the state of art denoising methods.