• Journal of the Korea Institute of Information Security & Cryptology
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• v.12 no.3
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• pp.77-85
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• 2002

A Research of binary random sequence generator that uses a linear shift register had been studied since the 1970s. These generators were used in stream cipher. In general, the binary random sequence generator consists of linear shift registers that generate sequences of maximum period and a nonlinear filter function or a nonlinear combination function to generate a sequence of high linear complexity. Therefore, To generate a sequence that have long period as well as high linear complexity becomes an important factor to estimate safety of stream cipher. Usually, the maximum period of the sequence generated by a linear feedback shift register with L resistors is less than or equal to $2^L$-1. In this paper, we propose new binary random sequence generator that consist of L registers and 2 sub-characteristic polynomials. According to an initial state vector, the least period of the sequence generated by the proposed generator is equal to or ions than it of the sequence created by the general linear feedback shift register, and its linear complexity is increased too.

• Proceedings of the IEEK Conference
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• 2002.06b
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• pp.109-112
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• 2002

This paper presents relationship between the dynamic behavior of an asynchronous linear pipeline (ALP) and the performance of the ALP as buffers are allocated. Then the relationship is used in order to characterize a local optimum situation on the buffer design space of the ALP. Using the characterization we propose an efficient algorithm optimizing buffer allocation on an ALP in order to achieve its average case performance. Without the loss of optimality, our algorithm works in linear time complexity so it achieves fast buffer-configuration optimization. This paper makes two contributions. First, it describes relationship between the performance characteristics of an ALP and a local optimum on the buffer design space of the ALP. Second, it devises a buffer allocation algorithm finding an optimum solution in linear time complexity.

• Journal of Broadcast Engineering
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• v.16 no.4
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• pp.624-634
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• 2011

Recently, the JCT-VC is developing the next generation video coding standard that is called HEVC. HEVC has adopted many coding technologies increasing coding efficiency. For chroma interpolation, DCT-based interpolation filter showing better performance than the linear filter in H.264/AVC was adopted in HEVC. In this paper, a combined filter that utilizes the FIR filter and the linear filter in H.264/AVC is proposed to increase coding efficiency. When the proposed method is compared with DCT-based interpolation filter, the experimental results for various sequences show that the average BD-rate improvements on chroma U and V components are 0.9% and 1.1%, respectively, in the high efficiency case of random access structure, those on U and V components are 1.1% and 1.1%, respectively, in the low complexity case of random access structure, those on U and V components are 0.9% and 1.4%, respectively, in the high efficiency case of low delay structure, and those on U and V components are 1.8% and 1.8%, respectively, in the low complexity case of low delay structure.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.3
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• pp.85-90
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• 2003

This paper proposes a modular multiplier based on LFSR (Linear Feedback Shift Register) architecture with efficient area complexity over GF(2/sup m/). At first, we examine the modular exponentiation algorithm and propose it's architecture, which is basic module for public-key cryptosystems. Furthermore, this paper proposes on efficient modular multiplier as a basic architecture for the modular exponentiation. The multiplier uses AOP (All One Polynomial) as an irreducible polynomial, which has the properties of all coefficients with '1 ' and has a more efficient hardware complexity compared to existing architectures.

• The Journal of Korea Robotics Society
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• v.5 no.1
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• pp.70-76
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• 2010

This paper addresses a design issue of "model complexity and performance trade-off" in the application of bandwidth extension (BWE) methods to the intra-frame predictivevector quantization problem of wideband speech. It discusses model-based linear and non-linear prediction methods and presents a comparative study of them in terms of prediction gain. Through experimentation, the general trend of saturation in performance (with the increase in model complexity) is observed. However, specifically, it is also observed that there is no significant difference between HMM and GMM-based BWE functions.

• East Asian mathematical journal
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• v.25 no.1
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• pp.55-68
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• 2009

In this paper we propose new large-update primal-dual inte-rior point algorithms for $P_*(\kappa)$ linear complementarity problems(LCPs). New search directions and proximity measures are proposed based on the kernel function$\psi(t)=\frac{t^{p+1}-1}{p+1}+\frac{e^{\frac{1}{t}}-e}{e}$,$p{\in}$[0,1]. We showed that if a strictly feasible starting point is available, then the algorithm has $O((1+2\kappa)(logn)^{2}n^{\frac{1}{p+1}}log\frac{n}{\varepsilon}$ complexity bound.

• Communications of the Korean Mathematical Society
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• v.32 no.1
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• pp.215-224
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• 2017

In this paper, we propose a method of order two for the computation of positive solutions to a boundary value problem of the linear beam equation. The method is based on the Power method for the eigenvector associated with the dominant eigenvalue and the Crout-like factorization algorithm for the banded system of linear equations. It is extremely fast due to the linear complexity of the linear system solver. Numerical result of a test problem is included.

• Phonetics and Speech Sciences
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• v.1 no.4
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• pp.127-132
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• 2009

The feature vectors which are used in conventional speaker recognition (SR) systems may have many correlations between their neighbors. To improve the performance of the SR, many researchers adopted linear transformation method like principal component analysis (PCA). In general, the linear transformation of the feature vectors is based on concatenated form of the static features and their dynamic features. However, the linear transformation which based on both the static features and their dynamic features is more complex than that based on the static features alone due to the high order of the features. To overcome these problems, we propose an efficient method that applies linear transformation and temporal information of the features to reduce complexity and improve the performance in speaker verification (SV). The proposed method first performs a linear transformation by PCA coefficients. The delta parameters for temporal information are then obtained from the transformed features. The proposed method only requires 1/4 in the size of the covariance matrix compared with adding the static and their dynamic features for PCA coefficients. Also, the delta parameters are extracted from the linearly transformed features after the reduction of dimension in the static features. Compared with the PCA and conventional methods in terms of equal error rate (EER) in SV, the proposed method shows better performance while requiring less storage space and complexity.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.4
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• pp.177-182
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• 2021

Generally, the linear programming (LP) with O(n⁴) time complexity is applied to mixture optimization problem that can be produce the given ingredients grade product with minimum cost from mixture of various raw materials. This paper suggests heuristic algorithm with O(n log n) time complexity to obtain the solution of this problem. The proposed algorithm meets the content range of the components required by the alloy steel plate while obtaining the minimum raw material cost, decides the quantity of raw material that is satisfied with ingredients grade for ascending order of unit cost. Although the proposed algorithm applies simple decision technique with O(n log n) time complexity, it can be obtains same solution as or more than optimization technique of linear programing.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.6
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• pp.1379-1392
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• 2018

The complexity of the differential-linear cryptanalysis is strongly influenced by the probability of the differential-linear characteristic computed under the assumption of round independence, linear approximation independence, and uniformity for the trail that does not satisfy differential trail. Therefore, computing the exact probability of the differential-linear characteristic is a very important issue related to the validity of the attack. In this paper, we propose a new concept called DLCT(Differential-Linear Connectivity Table) for the differential-linear cryptanalysis. Additionally, we propose an improved probability computation technique of differential-linear characteristic by applying DLCT. By doing so, we were able to weaken linear approximation independence assumption. We reanalyzed the previous results by applying DLCT to DES and SERPENT. The probability of 7-round differential-linear characteristic of DES is $1/2+2^{-5.81}$, the probability of 9-round differential-linear characteristic of SERPENT is computed again to $1/2+2^{-57.9}$, and data complexity required for the attack is reduced by $2^{0.2}$ and $2^{2.2}$ times, respectively.