• Bulletin of the Korean Mathematical Society
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• v.56 no.2
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• pp.277-283
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• 2019

In this paper, we present a cube root algorithm using a recurrence relation. Additionally, we compare the implementations of the Pocklington and $Padr{\acute{o}}-S{\acute{a}}ez$ algorithm with the Adleman-Manders-Miller algorithm. With the recurrence relations, we improve the Pocklington and $Padr{\acute{o}}-S{\acute{a}}ez$ algorithm by using a smaller base for exponentiation. Our method can reduce the average number of ${\mathbb{F}}_q$ multiplications.

• International Journal of Computer Science & Network Security
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• v.23 no.6
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• pp.84-90
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• 2023

In this article the problem of computing floating-point reciprocal cube root functions is considered. Our new algorithms for this task decrease the number of arithmetic operations used for computing $1/{\sqrt[3]{x}}$. A new approach for selection of magic constants is presented in order to minimize the computation time for reciprocal cube roots of arguments with movable decimal point. The underlying theory enables partitioning of the base argument range x∈[1,8) into 3 segments, what in turn increases accuracy of initial function approximation and decreases the number of iterations to one. Three best algorithms were implemented and carefully tested on 32-bit microcontroller with ARM core. Their custom C implementations were favourable compared with the algorithm based on cbrtf(x) function taken from C ＜math.h＞ library on three different hardware platforms. As a result, the new fast approximation algorithm for the function $1/{\sqrt[3]{x}}$ was determined that outperforms all other algorithms in terms of computation time and cycle count.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.5
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• pp.499-503
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• 2016

We study algorithms that can efficiently find cube roots by modifying Cipolla-Lehmer algorithm. In this paper, we present two type algorithms for finding cube roots in finite field, which improves Cipolla-Lehmer algorithm. If the number of multiplications of two type algorithms has a little bit of a difference, then it is more efficient algorithm which have less storage variables.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.37A no.12
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• pp.1031-1037
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• 2012

We study an algorithm that can efficiently find square roots and cube roots by modifying Tonelli-Shanks algorithm, which has an application in Number Field Sieve (NFS). The Number Field Sieve, the fastest known factoring algorithm, is a powerful tool for factoring very large integer. NFS first chooses two polynomials having common root modulo N, and it consists of the following four major steps; 1. Polynomial Selection 2. Sieving 3. Matrix 4. Square Root. The last step of NFS needs the process of square root computation in Number Field, which can be computed via square root algorithm over finite field.

• Journal of KIISE:Computer Systems and Theory
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• v.26 no.10
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• pp.1185-1193
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• 1999

최적 스택 필터는 시그널 또는 영상의 임의의 특성 정보를 보존하고자 하는 요구조건에 의해 강제된 구조적 제약 하에서 최대의 잡음제거 효과를 얻을 수 있다. 그리고 임계치 분할 특성과 양의 부울 함수에 기반한 이진 영역에서의 처리 특성은 이 필터가 높은 병렬성을 갖고 있음을 보여준다. 본 논문에서는 두 개의 병렬 계산 모델 MCC(Mesh-Connected Computer)와 CCC(Cube-Connected Computer)에서 최적 스택 필터를 위한 1차원 병렬 알고리즘을 개발한다. 최적 스택 필터의 실행 시간은 주로 이진 median 연산에 의해 결정되고 본 논문에서 제안된 알고리즘은 선형 분리성에 의해 이 연산을 구현한다. 이를 바탕으로, M 레벨의 1-D 시그널의 길이가 L이고 윈도우 폭이 N이라고 가정할 때, 제안된 알고리즘은 {{{{root M times root M`` MCC에서 O(L sqrt{M}`) 시간에 그리고 M 개의 PE를 갖는 CCC에서 O(L log M)시간에 수행될 수 있다. 또한 잡음을 더욱 효과적으로 제거하기 위해 윈도우 폭 N을 증가시킬 때, 제안된 병렬 알고리즘의 계산 시간은 일정하게 유지됨을 보인다.Abstract An optimal stack filter achieves the maximum noise attenuation under the structural constraints imposed by the requirement of preserving certain signal or image features. And the filter provides a high parallelism due to the principles of threshold decomposition and binary processing based on positive Boolean functions(PBFs). In this paper, we develop an one-dimensional parallel algorithm for the optimal stack filter on two parallel computation models, MCC(Mesh-Connected Computer) and CCC(Cube-Connected Computer). The running time of the optimal stack filter depends mainly on the binary median operation and our algorithm realizes this operation by the linear separability. Based on this scheme, our parallel algorithm can be performed in {{{{O(L sqrt{M}`) MCC and inO(L log M) time on CCC with M PEs, when the length of M``-valued 1-D signal is L`` and window width is N`` Also, we show that the computation time of our parallel algorithm keeps constant when the window width N increases in order to achieve the best noise attenuation.