• Journal of the Korean Statistical Society
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• v.22 no.1
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• pp.1-12
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• 1993

An approach to make the information bound sharper in median-unbiased estimation, based on an analogue of the Cramer-Rao inequality developed by Sung et al. (1990), is introduced for continuous densities with a nuisance parameter by considering information quantities contained both in the parametric function of interest and in the nuisance parameter in a linear fashion. This approach is comparable to that of improving the information bound in mean-unbiased estimation for the case of two unknown parameters. Computation of an optimal weight corresponding to the nuisance parameter is also considered.

• Journal of the Korean Statistical Society
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• v.28 no.1
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• pp.35-44
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• 1999

We derive a new upper bound of convolution type for the median-unbiased estimators with respect to an arbitrary unimodal utility functions. We also obtain the necessary and sufficient condition for the attainability of the information bound. Applications to general MLR(Monotone Likelihood Ratio) model and censored survival data re discussed as examples.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3557-3571
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• 2014

We develop a secret key generation scheme using phase estimation in ultra-wideband (UWB) wireless fading channels. Based on the reciprocity theorem, two terminals extract the phase of the channel as a common random source to generate secret bits. Moreover, we study the secret key rate by a pair of nodes observing correlated sources and communicating to achieve secret key agreement over public communication channels. As our main results, we establish a more practical upper bound from Cramer-Rao bound (CRB) and compare it with a universally theoretical upper bound on the shared maximum key rate from mutual information of correlated random sources. Derivation and numerical examples are presented to demonstrate the bound. Simulation studies are also provided to validate feasibility and efficiency of the proposed scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.8C
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• pp.750-755
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• 2009

Tomlinson-Harashima precoding (THP) is considered as a prominent precoding scheme due to its capability to cancel out the known interference at the transmitter side. Therefore, the information rates achieved by THP are superior to those achieved by conventional linear precoding schemes. In this paper, a new lower bound on the achievable information rate by the regularized THP under additive white Gaussian noise (AWGN) channel with multiuser interference is derived. Analytical results show that the lower bound derived in this paper is tighter than the original lower bound particularly at low SNR range, while both lower bounds converge to the same lower limit as SNR$\rightarrow$$\infty$.

• Journal of Korea Multimedia Society
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• v.13 no.12
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• pp.1798-1804
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• 2010

TCP with AIMD mechanism, one of the most popular protocols in internet, can solve congestion control in wired networks. This protocol, however, is not efficient in wireless networks. This paper proposes a new mechanism namely General AIMD with Congestion Window Upper Bound in which congestion window is limited by an upper bound. By applying optimization theory, we find an optimal policy for congestion window upper bound to maximize network throughput.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.39
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• pp.9-18
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• 1996

Many algorithms have been developed for optimizing the asymmectric traveling salesman problem known as a representative NP-Complete problem. The most efficient ones of them are branch and bound algorithms based on the subtour elimination approach. To increase efficiency of the branch and bound algorithm. number of decision nodes should be decreased. For this the minimum bound that is more close at the optimal solution should be found or an effective bounding strategy should be used. If the optimal solution has been known, we may apply it usefully to branching. Because a good feasible solution should be found as soon as possible and have similar features of the optimal solution. By the way, the upper bound solution in branch and bound algorithm is most close at the optimal solution. Therefore, the upper bound solution can be used instead of the optimal solution and information of which can be applied to new branching criteria. As mentioned above, this paper will propose an effective branching rule using the information of the upper bound solution in the branch and bound algorithm. And superiority of the new branching rule will be shown by comparing with Bellmore-Malone's one and carpaneto-Toth's one that were already proposed.

• Proceedings of the IEEK Conference
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• 2002.07c
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• pp.1780-1783
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• 2002

A problem of signal transmitted and received in OFDM systems is considered. In particular, an efficient solution to the problem of blind channel estimation based on Maximum Likelihood (ML) principle has been investigated. The paper proposes a new upper-bound cost, used in conjunction with a standard branch and bound integer programming technique for solving the ML problem. The tighter upper-bound cost exploits a finite-alphabet property of the transmitted signal. The proposed upper-bound cost was found to greatly speed up the ML algorithm, thus reducing computational complexity. Experimental results and discussion are included.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1219-1231
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• 2008

The main object of this paper is to develop a leave-one-out(LOO) bound of all pairwise comparison error correcting output codes (APC-ECOC). To avoid using classifiers whose corresponding target values are 0 in APC-ECOC and requiring pilot estimates we developed a bound based on mean misclassification probability(MMP). It can be used to tune kernel hyperparameters. Our empirical experiment using kernel mean squared estimate(KMSE) as the binary classifier indicates that the bound leads to good estimates of kernel hyperparameters.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.10
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• pp.3624-3637
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• 2014

At SAC 2004, Junod and Vaudenay designed the FOX family based on the Lai-Massey scheme. They noted that it was impossible to find any useful differential characteristic or linear trail after 8 rounds of FOX64 or FOX128. In this paper, we provide the lower bound of differentially active S-boxes in consecutive rounds of the Lai-Massey scheme that has SPS as its F-function, and we propose the necessary conditions for the reachability of the lower bound. We demonstrate that similar results can be obtained with respect to the lower bound of linearly active S-boxes by proving the duality in the Lai-Massey scheme. Finally, we apply these results to FOX64 and FOX128 and prove that it is impossible to find any useful differential characteristics or linear trail after 6 rounds of FOX64. We provide a more precise security bound for FOX128.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.5-9
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• 2008

Researchers have investigated many upper bound techniques applicable to error probabilities on the maximum likelihood (ML) decoding performance of turbo-like codes and low density parity check (LDPC) codes in recent years for a long codeword block size. This is because it is trivial for a short codeword block size. Previous research efforts, such as the simple bound technique [20] recently proposed, developed upper bounds for LDPC codes and turbo-like codes using ensemble codes or the uniformly interleaved assumption. This assumption bounds the performance averaged over all ensemble codes or all interleavers. Another previous research effort [21] obtained the upper bound of turbo-like code with a particular interleaver using a truncated union bound which requires information of the minimum Hamming distance and the number of codewords with the minimum Hamming distance. However, it gives the reliable bound only in the region of the error floor where the minimum Hamming distance is dominant, i.e., in the region of high signal-to-noise ratios. Therefore, currently an upper bound on ML decoding performance for turbo-like code with a particular interleaver and LDPC code with a particular parity check matrix cannot be calculated because of heavy complexity so that only average bounds for ensemble codes can be obtained using a uniform interleaver assumption. In this paper, we propose a new bound technique on ML decoding performance for turbo-like code with a particular interleaver and LDPC code with a particular parity check matrix using ML estimated weight distributions and we also show that the practical iterative decoding performance is approximately suboptimal in ML sense because the simulation performance of iterative decoding is worse than the proposed upper bound and no wonder, even worse than ML decoding performance. In order to show this point, we compare the simulation results with the proposed upper bound and previous bounds. The proposed bound technique is based on the simple bound with an approximate weight distribution including several exact smallest distance terms, not with the ensemble distribution or the uniform interleaver assumption. This technique also shows a tighter upper bound than any other previous bound techniques for turbo-like code with a particular interleaver and LDPC code with a particular parity check matrix.