• 한국경영과학회:학술대회논문집
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• 대한산업공학회/한국경영과학회 1996년도 춘계공동학술대회논문집; 공군사관학교, 청주; 26-27 Apr. 1996
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• pp.24-29
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• 1996

If the LP problem doesn't have the optimal soultion uniquely, the solution fo the primal-dual barrier method converges to the interior point of the optimal face. Therefore, when the optimal vertex solution or the optimal basis is required, we have to perform the additional procedure to recover the optimal basis from the final solution of the interior point method. In this paper the exisiting methods for recovering the optimal basis or identifying the optimal solutions are analyzed and the new methods are suggested. This paper treats the two optimal basis recovery methods. One uses the purification scheme and the simplex method, the other uses the optimal face solutions. In the method using the purification procedure and the simplex method, the basic feasible solution is obtained from the given interior solution and then simplex method is performed for recovering the optimal basis. In the method using the optimal face solutions, the optimal basis in the primal-dual barrier method is constructed by intergrating the optimal solution identification technique and the optimal basis extracting method from the primal-optimal soltion and the dual-optimal solution.

• 한국전자거래학회지
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• 제8권1호
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• pp.113-119
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• 2003

This paper proposes a new multiplicative inverse algorithm for the Galois field GF (2/sup m/) whose elements are represented by optimal normal basis type Ⅱ. One advantage of the normal basis is that the squaring of an element is computed by a cyclic shift of the binary representation. A normal basis element is always possible to rewrite canonical basis form. The proposed algorithm combines normal basis and canonical basis. The new algorithm is more suitable for implementation than conventional algorithm.

• Management Science and Financial Engineering
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• 제10권2호
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• pp.103-118
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• 2004

$\epsilon$-sensitivity analysis is a kind of methods for performing sensitivity analysis for linear programming. Its main advantage is that it can be directly applied for interior-point methods with a little computation. Although $\epsilon$-sensitivity analysis was proposed several years ago, there have been no studies on its relationship with other sensitivity analysis methods. In this paper, we discuss the relationship between $\epsilon$-sensitivity analysis and sensitivity analysis using an optimal basis. First. we present a property of $\epsilon$-sensitivity analysis, from which we derive a simplified formula for finding the characteristic region of $\epsilon$-sensitivity analysis. Next, using the simplified formula, we examine the relationship between $\epsilon$-sensitivity analysis and sensitivity analysis using optimal basis when an $\epsilon$-optimal solution is sufficiently close to an optimal extreme solution. We show that under primal nondegeneracy or dual non degeneracy of an optimal extreme solution, the characteristic region of $\epsilon$-sensitivity analysis converges to that of sensitivity analysis using an optimal basis. However, for the case of both primal and dual degeneracy, we present an example in which the characteristic region of $\epsilon$-sensitivity analysis is different from that of sensitivity analysis using an optimal basis.

• 한국경영과학회지
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• 제16권1호
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• pp.89-96
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• 1991

When a feasible solution approaches to the optimal extreme point in Karmakar's algorithm, components of the search direction vector for a solution converge at a certain value according to the corresponding columns of the optimal basis and the optimal nonbasis. By using this convergence properties of Karmarkar's algorithm, we can identify columns of the optimal basis before the final stage of the algorithm. The complexity of Karmarker's algorithm with newly proposed termination criterion does not increase. A numerical experiments for the problems which were generated by random numbers are also illustrated. Experimental results show that the number of iterations required for determining columns of the optimal basis depends on problems. For all cases, however, columns of the optimal basis are exactly verified when this termination criterion is used.

• 한국통신학회논문지
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• 제34권1C호
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• pp.21-27
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• 2009

지수의 signed digit representation을 사용하여 타입 II 최적정규기저에 의해 결정되는 $GF(2^n)$상의 효율적인 지수승 알고리즘을 제안한다. 제안하는 signed digit representation은 $GF(2^n)$에서 non-adjacent form(NAF)를 사용한다. 일반적으로 signed digit representation은 정규기저가 주어진 경우 사용하기 어렵다. 이는 정규 원소의 역원연산이 상당한 지연시간을 갖기 때문이다. 반면에 signed digit representation은 다항식 기저를 이용한 체에 쉽게 적용가능하다. 하지만 본 논문의 결과는 타입 II 최적정규기저(optimal normal basis, ONB), 라는 특별한 정규 기저가 지수의 signed digit representation을 이용한 효율적인 지수승 연산에 이용될 수 있음을 보인다.

• 정보보호학회논문지
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• 제9권4호
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• pp.3-10
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• 1999

유한체(Galois fields)가 타원곡선 암호법 coding 이론 등에 응용되면서 유한체의 연 산은 더많은 관심의 대상이 되고 있다. 유한체의 연산은 표현방법에 많은 영향을 받는다. 즉 최적 정규기 저는 하드웨 어 구현에 용이하고 Trinomial을 이용한 다항식 기저는 소프트웨어 구현에 효과적이다. 이논문에서는 새로운 변형된 다항식 기저를 소개하고 AOP를 이용한 경우 하드웨어 구현에 효과적인 최 적 정규기저와 의 변환이 위치 변화로 이루어지고 또한 이것을 바탕으로 한 유한체의 연산이 소프트웨어적 으로 효율적 임을 보인다. More concerns are concentrated in finite fields arithmetic as finite fields being applied for Elliptic curve cryptosystem coding theory and etc. Finite fields arithmetic is affected in represen -tation of those. Optimal normal basis is effective in hardware implementation and polynomial field which is effective in the basis conversion with optimal normal basis and show that the arithmetic of finite field with the basis is effective in software implementation.

• ETRI Journal
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• 제30권2호
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• pp.326-334
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• 2008

This paper proposes a method for generating a basis translation matrix between isomorphic extension fields. To generate a basis translation matrix, we need the equality correspondence of a basis between the isomorphic extension fields. Consider an extension field $F_{p^m}$ where p is characteristic. As a brute force method, when $p^m$ is small, we can check the equality correspondence by using the minimal polynomial of a basis element; however, when $p^m$ is large, it becomes too difficult. The proposed methods are based on the fact that Type I and Type II optimal normal bases (ONBs) can be easily identified in each isomorphic extension field. The proposed methods efficiently use Type I and Type II ONBs and can generate a pair of basis translation matrices within 15 ms on Pentium 4 (3.6 GHz) when $mlog_2p$ = 160.

• Journal of Mechanical Science and Technology
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• 제19권spc1호
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• pp.452-460
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• 2005

Based on an introduced optimal trajectory planning method, this paper mainly deals with the accuracy analysis during the function approximation process of the optimal trajectory planning method. The basis functions are composed of Hermit polynomials and Fourier series to improve the approximation accuracy. Since the approximation accuracy is affected by the given orders of each basis function, the accuracy of the optimal solution is examined by changing the combinations of the orders of Hermit polynomials and Fourier series as the approximation basis functions. As a result, it is found that the proper approximation basis functions are the $5^{th}$ order Hermit polynomials and the $7^{th}-10^{th}$ order of Fourier series.

• 호남수학학술지
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• 제29권3호
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• pp.415-425
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• 2007

The normal basis has the advantage that the result of squaring an element is simply the right cyclic shift of its coordinates in hardware implementation over finite fields. In particular, the optimal normal basis is the most efficient to hardware implementation over finite fields. In this paper, we propose an efficient parallel architecture which transforms the Gaussian normal basis multiplication in GF($2^m$) into the type-I optimal normal basis multiplication in GF($2^{mk}$), which is based on the palindromic representation of polynomials.

• 경영과학
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• 제17권2호
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• pp.1-12
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• 2000

In this study, we deals with the implementation of an optimal basis identification procedure for interior point methods. Our implementation is based on Megiddo’s strongly polynomial algorithm applied to Andersen and Ye’s approximate LP construction. Several techniques are explained such as the use of effective indicator for obtaining optimal partition when constructing the approximate LP, the efficient implementation of the problem reduction technique proposed by Andersen, the crashing procedure needed for fast dual phase of Megiddo’s algorithm and the construction of the stable initial basis. By experimental comparison, we show that our implementation is superior to the crossover scheme implementation.