• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.13 no.3
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• pp.189-202
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• 2009

In this paper we propose new primal-dual interior point algorithms for $P_*(\kappa)$ linear complementarity problems based on a new class of kernel functions which contains the kernel function in [8] as a special case. We show that the iteration bounds are $O((1+2\kappa)n^{\frac{9}{14}}\;log\;\frac{n{\mu}^0}{\epsilon}$) for large-update and $O((1+2\kappa)\sqrt{n}log\frac{n{\mu}^0}{\epsilon}$) for small-update methods, respectively. This iteration complexity for large-update methods improves the iteration complexity with a factor $n^{\frac{5}{14}}$ when compared with the method based on the classical logarithmic kernel function. For small-update, the iteration complexity is the best known bound for such methods.

• Bulletin of the Korean Mathematical Society
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• v.46 no.3
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• pp.521-534
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• 2009

In this paper we present new large-update primal-dual interior point algorithms for $P_*$ linear complementarity problems(LAPS) based on a class of kernel functions, ${\psi}(t)={\frac{t^{p+1}-1}{p+1}}+{\frac{1}{\sigma}}(e^{{\sigma}(1-t)}-1)$, p $\in$ [0, 1], ${\sigma}{\geq}1$. It is the first to use this class of kernel functions in the complexity analysis of interior point method(IPM) for $P_*$ LAPS. We showed that if a strictly feasible starting point is available, then new large-update primal-dual interior point algorithms for $P_*$ LAPS have $O((1+2+\kappa)n^{{\frac{1}{p+1}}}lognlog{\frac{n}{\varepsilon}})$ complexity bound. When p = 1, we have $O((1+2\kappa)\sqrt{n}lognlog\frac{n}{\varepsilon})$ complexity which is so far the best known complexity for large-update methods.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1998.04a
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• pp.70-74
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• 1998

Liner complexity(LC), which could quantify the modal structure, were calculated from electroencephalograms(EEGs) in four states such as a pleasant and relaxed, a pleasant and aroused, an unpleasant and relaxed, and an unpleasant and aroused state. Each state was evoke by visual stimuli of relaxed or aroused state, LC could discriminate statistically state(t-test; p<0.01). LCs in pleasant states were larger than those in unpleasant ones.

• The Journal of the Korea institute of electronic communication sciences
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• v.10 no.11
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• pp.1231-1238
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• 2015

In this paper, we proposed an efficient algorithm using Node monitoring (NM) and Piecewise Linear Function Approximation(: NP) for reducing the complexity of LDPC code decoding. Proposed NM algorithm is based on a new node-threshold method together with message passing algorithm. Piecewise linear function approximation is used to reduce the complexity of the algorithm. This new algorithm was simulated in order to verify its efficiency. Complexity of our new NM algorithm is improved to about 20% compared with well-known methods according to simulation results.

• Journal of Communications and Networks
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• v.9 no.1
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• pp.75-83
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• 2007

Orthogonal frequency division multiplexing (OFDM) systems with multiple transmit antennas can exploit space-time block coding on each subchannel for reliable data transmission. Spacetime coded OFDM systems, however, are very sensitive to time variant channels because the channels need to be static over multiple OFDM symbol periods. In this paper, we propose to mitigate the channel variations in the frequency domain using a linear filter in the frequency domain that exploits the sparse structure of the system matrix in the frequency domain. Our approach has reduced complexity compared with alternative approaches based on time domain block-linear filters. Simulation results demonstrate that our proposed frequency domain block-linear filter reduces computational complexity by more than a factor of ten at the cost of small performance degradation, compared with a time domain block-linear filter.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.506-509
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• 2009

This paper studies about reducing the complexity of ML detection in MIMO/V-blast system, based on MMSE and ZF linear detectors. Beforehand, the receiver detects the signal using the linear detector such as ZF or MMSE. Moreover, the next step is to assess whether the signal is reliable or not by verifying the reliability condition, if the latter is reliable then it is the output if not it has to be detected by the advanced detector until the reliability condition is verified.

• ETRI Journal
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• v.32 no.4
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• pp.588-595
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• 2010

This paper proposes encoding and decoding for nonlinear product codes and investigates the performance of nonlinear product codes. The proposed nonlinear product codes are constructed as N-dimensional product codes where the constituent codes are nonlinear binary codes derived from the linear codes over higher order alphabets, for example, Preparata or Kerdock codes. The performance and the complexity of the proposed construction are evaluated using the well-known nonlinear Nordstrom-Robinson code, which is presented in the generalized array code format with a low complexity trellis. The proposed construction shows the additional coding gain, reduced error floor, and lower implementation complexity. The (64, 24, 12) nonlinear binary product code has an effective gain of about 2.5 dB and 1 dB gain at a BER of $10^{-6}$ when compared to the (64, 15, 16) linear product code and the (64, 24, 10) linear product code, respectively. The (256, 64, 36) nonlinear binary product code composed of two Nordstrom-Robinson codes has an effective gain of about 0.7 dB at a BER of $10^{-5}$ when compared to the (256, 64, 25) linear product code composed of two (16, 8, 5) quasi-cyclic codes.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.12 no.4
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• pp.227-238
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• 2008

In this paper we extend primal-dual interior point algorithm for linear optimization (LO) problems to $P_*({\kappa})$ linear complementarity problems(LCPs) ([1]). We define proximity functions and search directions based on kernel functions, ${\psi}(t)=\frac{t^{p+1}-1}{p+1}-{\log}\;t$, $p{\in}$[0, 1], which is a generalized form of the one in [16]. It is the first to use this class of kernel functions in the complexity analysis of interior point method(IPM) for $P_*({\kappa})$ LCPs. We show that if a strictly feasible starting point is available, then new large-update primal-dual interior point algorithms for $P_*({\kappa})$ LCPs have $O((1+2{\kappa})nlog{\frac{n}{\varepsilon}})$ complexity which is similar to the one in [16]. For small-update methods, we have $O((1+2{\kappa})\sqrt{n}{\log}{\frac{n}{\varepsilon}})$ which is the best known complexity so far.

• Journal of applied mathematics & informatics
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• v.29 no.5_6
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• pp.1285-1293
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• 2011

We establishes the polynomial convergence of a new class of path-following methods for semidefinite linear complementarity problems (SDLCP) whose search directions belong to the class of directions introduced by Monteiro [9]. Namely, we show that the polynomial iteration-complexity bound of the well known algorithms for linear programming, namely the predictor-corrector algorithm of Mizuno and Ye, carry over to the context of SDLCP.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.1
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• pp.25-29
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• 2001

We present a two dimensional linear programming knapsack problem with the extended GUB constraint. The presented problem is an extension of the cardinality constrained linear programming knapsack problem. We identify some new properties of the problem and derive a solution algorithm based on the parametric analysis for the knapsack right-hand-side. The solution algorithm has a worst case time complexity of order O($n^2logn$). A numerical example is given.