• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.59-62
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• 1999

CDMA receiving algorithms, such as single/multi user detector and smart antenna system which have been proposed to suppress ISI and MAI. still suffer from the residual interferences among the output signals. A blind adaptive CMA post-processing technique, which is able to suppress the residual ISI and MAI symbol-by-symbol was proposed. It can be easily applied to any conventional detector at the expense of a small amount of additional computations. In this paper, a solution for the convergence problem of proposed method is proposed and analyzed. Through computer simulations it was shown that the proposed method has stable convergence property and good performance in BER.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1011-1014
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• 1999

In this paper, a new algorithm has been presented that helps to preserve diversity as well as to enhance the convergence speed of the evolutionary programming. This algorithm is based on the cell partitioning of search region for preserving the diversity. Until now, the greater part of researches is not concerned about preserving the diversity of individuals in a population but improving convergence speed. Although these evolutions are started from multi-point search at the early phase, but at the end those search points are swarming about a one-point, the strong candidate. These evolutions vary from the original idea in some points such as multi-point search. In most case we want to find the only one point of the best solution not several points in the vicinity of that. That is why the cell partitioning of search region has been used. By restricting the search area of each individual, the diversity of individual in solution space is preserved and the convergence speed is enhanced. The efficiency of the proposed algorithm has been verified through benchmark test functions.

• Journal of the Korean Mathematical Society
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• v.51 no.4
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• pp.679-702
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• 2014

Investigation of the numerical solution of singularly perturbed turning point problems dates back to late 1970s. However, due to the presence of layers, not many high order schemes could be developed to solve such problems. On the other hand, one could think of applying the convergence acceleration technique to improve the performance of existing numerical methods. However, that itself posed some challenges. To this end, we design and analyze a novel fitted operator finite difference method (FOFDM) to solve this type of problems. Then we develop a fitted mesh finite difference method (FMFDM). Our detailed convergence analysis shows that this FMFDM is robust with respect to the singular perturbation parameter. Then we investigate the effect of Richardson extrapolation on both of these methods. We observe that, the accuracy is improved in both cases whereas the rate of convergence depends on the particular scheme being used.

• Journal of Communications and Networks
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• v.17 no.4
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• pp.384-393
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• 2015

This paper proposes an insect behavior-inspired routing algorithm for large-scale wireless mesh networks. The proposed algorithm is adapted from the behavior of an insect called Bombyx mori, a male silkmoth. Its unique behavior is its flying technique to find the source of pheromones. The algorithm consists of two steps: the shortest-path algorithm and the zigzag-path algorithm. First, the shortest-path algorithm is employed to transmit data. After half of the total hops, the zigzag-path algorithm, which is based on the movement of the male B. mori, is applied. In order to adapt the biological behavior to large-scale wireless mesh networks, we use a mesh topology for implementing the algorithm. Simulation results show that the total energy used and the decision time for routing of the proposed algorithm are improved under certain conditions.

• Journal of the Institute of Convergence Signal Processing
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• v.11 no.3
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• pp.238-243
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• 2010

A new implementation method for MPDSAP(Maximally Polyphase Decomposed Subband Affine Projection) adaptive filter is proposed. The affine projection(AP) adaptive filter achieves fast convergence speed, however, its implementation is so expensive because of the matrix inversion for a weight-updating of adaptive filter. The maximally polyphase decomposed subband filtering allows the AP adaptive filter to avoid the matrix inversion, moreover, by using a pipelining technique, the simple subband structured AP is suitable for VLSI implementations concerning throughput, power dissipation and area. Computer simulations are presented to verify the performance of the proposed algorithm.

• Journal of electromagnetic engineering and science
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• v.9 no.1
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• pp.12-16
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• 2009

This paper presents a new iterative locally one-dimensional [mite-difference time-domain(LOD-FDTD) method that has a simpler formula than the original iterative LOD-FDTD formula[l]. There are fewer arithmetic operations than in the original LOD-FDTD scheme. This leads to a reduction of CPU time compared to the original LOD-FDTD method while the new method exhibits the same numerical accuracy as the iterative ADI-FDTD scheme. The number of arithmetic operations shows that the efficiency of this method has been improved approximately 20 % over the original iterative LOD-FDTD method.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1998.10a
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• pp.84-91
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• 1998

A numerically stable technique to remove tile limitation in choosing a shift in the subspace iteration method with shift is presented. A major difficulty of the subspace iteration method with shift is that because of singularity problem, a shift close to an eigenvalue can not be used, resulting in slower convergence. This study selves the above singularity problem using side conditions without sacrifice of convergence. The method is always nonsingular even if a shiht is an eigenvalue itself. This is one of tile significant characteristics of the proposed method. The nonsingularity is proved analytically. The convergence of the proposed method is at least equal to that of the subspace iteration method with shift, and the operation counts of above two methods are almost the same when a large number of eigenpairs are required. To show the effectiveness of the proposed method, two numerical examples are considered

• ETRI Journal
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• v.31 no.6
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• pp.755-764
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• 2009

This paper presents a switched self-biasing and a tail current-shaping technique to suppress the 1/f noise from a tail current source in differential cross-coupled inductance-capacitance (LC) voltage-controlled oscillators (VCOs). The proposed LC VCO has an amplitude control characteristic due to the creation of negative feedback for the oscillation waveform amplitude. It is fabricated using a 0.13 ${\mu}m$ CMOS process. The measured phase noise is -117 dBc/Hz at a 1 MHz offset from a 4.85 GHz carrier frequency, while it draws 6.5 mA from a 0.6 V supply voltage. For frequency tuning, process variation, and temperature change, the amplitude change rate of the oscillation waveform in the proposed VCO is 2.1 to 3.2 times smaller than that of an existing VCO with a fixed bias. The measured amplitude change rate of the oscillation waveform for frequency tuning from 4.55 GHz to 5.04 GHz is 131 pV/Hz.

• International Journal of Control, Automation, and Systems
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• v.6 no.2
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• pp.171-179
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• 2008

This paper addresses the synthesis of an iterative learning controller for a class of linear systems with norm-bounded parameter uncertainties. We take into account an iterative learning algorithm with current cycle feedback in order to achieve both robust convergence and robust stability. The synthesis problem of the developed iterative learning control (ILC) system is reformulated as the ${\gamma}$-suboptimal $H_{\infty}$ control problem via the linear fractional transformation (LFT). A sufficient convergence condition of the ILC system is presented in terms of linear matrix inequalities (LMIs). Furthermore, the ILC system with fast convergence rate is constructed using a convex optimization technique with LMI constraints. The simulation results demonstrate the effectiveness of the proposed method.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.8
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• pp.92-103
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• 1997

This paper proposes a new gray-level image segmentation method using GA(genetic algorithm) and an ACA(adaptive clustering algorithm). The solution in the general GA can be moving because of stochastic reinsertion, and suffer from the premature convergence problem owing to deficiency of individuals before finding the optimal solution. To cope with these problems and to reduce processing time, we propose the new GBR algorithm and the technique that resolves the premature convergence problem. GBR selects the individual in the child pool that has the fitness value superior to that of the individual in the parents pool. We resolvethe premature convergence problem with producing the mutation in the parents population, and propose the new method that removes the small regions in the segmented results. The experimental results show that the proposed segmentation algorithm gives better perfodrmance than the ACA ones in Gaussian noise environments.