• Title/Summary/Keyword: Subset sum

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AN UPPER BOUND OF THE RECIPROCAL SUMS OF GENERALIZED SUBSET-SUM-DISTINCT SEQUENCE

  • Bae, Jaegug
    • Journal of the Chungcheong Mathematical Society
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    • v.21 no.2
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    • pp.223-230
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    • 2008
  • In this paper, we present an upper bound of the reciprocal sums of generalized subset-sum-distinct sequences with respect to the first terms of the sequences. And we show the suggested upper bound is best possible. This is a kind of generalization of [1] which contains similar result for classical subset-sum-distinct sequences.

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A GENERALIZATION OF A SUBSET-SUM-DISTINCT SEQUENCE

  • Bae, Jae-Gug;Choi, Sung-Jin
    • Journal of the Korean Mathematical Society
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    • v.40 no.5
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    • pp.757-768
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    • 2003
  • In 1967, as an answer to the question of P. Erdos on a set of integers having distinct subset sums, J. Conway and R. Guy constructed an interesting sequence of sets of integers. They conjectured that these sets have distinct subset sums and that they are close to the best possible with respect to the largest element. About 30 years later (in 1996), T. Bohman could prove that sets from the Conway-Guy sequence actually have distinct subset sums. In this paper, we generalize the concept of subset-sum-distinctness to k-SSD, the k-fold version. The classical subset-sum-distinct sets would be 1-SSD in our definition. We prove that similarly derived sequences as the Conway-Guy sequence are k-SSD.

SOME REMARKS ON PROBLEMS OF SUBSET SUM

  • Min, Tang;Hongwei, Xu
    • Bulletin of the Korean Mathematical Society
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    • v.59 no.6
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    • pp.1339-1348
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    • 2022
  • Let A = {a1 < a2 < ⋯} be a sequence of integers and let P(A) = {Σεiai : ai ∈ A, εi = 0 or 1, Σεi < ∞}. Burr posed the following question: Determine conditions on integers sequence B that imply either the existence or the non-existence of A for which P(A) is the set of all non-negative integers not in B. In this paper, we focus on some problems of subset sum related to Burr's question.

Hidden Subset Sum 문제를 이용한 Chor-Rivest 암호체계

  • 이희정
    • Review of KIISC
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    • v.9 no.4
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    • pp.81-87
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    • 1999
  • Density'(밀도)가 비교적 높은 Chor-Rivest 암호체계는 기존의 LLL과 같은 유형의 공격법이 아니라 비밀키를 일부 찾아내므로 써 공격이 가능하고 '98 Crypto에 처음 발표되 고 '99 Crypto에 그의 공격법과 안전성이 논의된 hidden subset sum problem은 기존의 knapsack 유형의 암호체계와 마찬가지로 밀도가 높을 때 안전하고 밀도가 낮으면 공격이 가능하다 따라서 두 암호체계의 접목을 통하여 안전한 암호체계가 가능한지를 살펴보는 것 도 의미가 있을 것이다, 결론적으로 이야기하면 두암호체계의 접목은 여러 가지 문제점을 포함하고 있기 때문에 어려우리라 생각된다. 제1장에서의 hidden subset sum problem을 살 펴보고 제2장에서는 Chor-Rivest 암호체계를 분석해보고 제 3장에서 Chor-Rivest 암호체계 의 변경 가능한 요소들을 살펴보고 제4장에서 Chor-Rivest 암호체계에 hidden subset sum problem의 활용이 가능한지를 살펴보도록한다. knapsack 유형의 암호체계들중 비교적 최근 까지 안전하다고 하는 암호체계들을 살펴봄으로써 이런 유형들의 개발여부를 생각해 볼수 있는 기회가 되리라 기대된다.

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A COMPACTNESS RESULT FOR A SET OF SUBSET-SUM-DISTINCT SEQUENCES

  • Bae, Jae-Gug
    • Bulletin of the Korean Mathematical Society
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    • v.35 no.3
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    • pp.515-525
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    • 1998
  • In this paper we obtain a "compactness" result that asserts the existence, in certain sets of sequences, of a sequence which has a maximal reciprocal sum. We derive this result from a much more general theorem which will be proved by introducing a metric into the set of sequences and using a topological argument.

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Performance Comparison between Genetic Algorithms and Dynamic Programming in the Subset-Sum Problem (부분집합 합 문제에서의 유전 알고리즘과 동적 계획법의 성능 비교)

  • Cho, Hwi-Yeon;Kim, Yong-Hyuk
    • Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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    • v.8 no.4
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    • pp.259-267
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    • 2018
  • The subset-sum problem is to find out whether or not the element sum of a subset within a finite set of numbers is equal to a given value. The problem is a well-known NP-complete problem, which is difficult to solve within a polynomial time. Genetic algorithm is a method for finding the optimal solution of a given problem through operations such as selection, crossover, and mutation. Dynamic programming is a method of solving a given problem from one or several subproblems. In this paper, we design and implement a genetic algorithm that solves the subset-sum problem, and experimentally compared the time performance to find the answer with the case of dynamic programming method. We selected a total of 17 test cases considering the difficulty in a set with 63 elements of positive number, and compared the performance of the two algorithms. The presented genetic algorithms showed time performance improved by 84% on 13 of 17 problems when compared with dynamic programming.

A Generalized Subtractive Algorithm for Subset Sum Problem (부분집합 합 문제의 일반화된 감산 알고리즘)

  • Lee, Sang-Un
    • The Journal of the Institute of Internet, Broadcasting and Communication
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    • v.22 no.2
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    • pp.9-14
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    • 2022
  • This paper presents a subset sum problem (SSP) algorithm which takes the time complexity of O(nlogn). The SSP can be classified into either super-increasing sequence or random sequence depending on the element of Set S. Additive algorithm that runs in O(nlogn) has already been proposed to and utilized for the super-increasing sequence SSP, but exhaustive Brute-Force method with time complexity of O(n2n) remains as the only viable algorithm for the random sequence SSP, which is thus considered NP-complete. The proposed subtractive algorithm basically selects a subset S comprised of values lower than target value t, then sets the subset sum less the target value as the Residual r, only to remove from S the maximum value among those lower than t. When tested on various super-increasing and random sequence SSPs, the algorithm has obtained optimal solutions running less than the cardinality of S. It can therefore be used as a general algorithm for the SSP.

Self-adaptive and Bidirectional Dynamic Subset Selection Algorithm for Digital Image Correlation

  • Zhang, Wenzhuo;Zhou, Rong;Zou, Yuanwen
    • Journal of Information Processing Systems
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    • v.13 no.2
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    • pp.305-320
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    • 2017
  • The selection of subset size is of great importance to the accuracy of digital image correlation (DIC). In the traditional DIC, a constant subset size is used for computing the entire image, which overlooks the differences among local speckle patterns of the image. Besides, it is very laborious to find the optimal global subset size of a speckle image. In this paper, a self-adaptive and bidirectional dynamic subset selection (SBDSS) algorithm is proposed to make the subset sizes vary according to their local speckle patterns, which ensures that every subset size is suitable and optimal. The sum of subset intensity variation (${\eta}$) is defined as the assessment criterion to quantify the subset information. Both the threshold and initial guess of subset size in the SBDSS algorithm are self-adaptive to different images. To analyze the performance of the proposed algorithm, both numerical and laboratory experiments were performed. In the numerical experiments, images with different speckle distribution, different deformation and noise were calculated by both the traditional DIC and the proposed algorithm. The results demonstrate that the proposed algorithm achieves higher accuracy than the traditional DIC. Laboratory experiments performed on a substrate also demonstrate that the proposed algorithm is effective in selecting appropriate subset size for each point.

PREORDERINGS ON LOCAL GLOBAL RINGS

  • Shin, Kee-Young
    • Journal of the Chungcheong Mathematical Society
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    • v.8 no.1
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    • pp.105-110
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    • 1995
  • Suppose A is a local global ring (with many units) and $T{\subset}A$ is a preordering. Let $a_i{\in}A^*$, $i=1,2,{\cdots},n$ and $a{\in}({\sum}_{i=1}^{l-1}\;a_iT){\cap}A^*$. Then, for any integer l, 1 < l ${\leq}$ n, there exist $x{\in}({\sum}_{i=1}^{l-1}\;a_iT){\cap}A^*$ and $y{\in}({\sum}_{i=l}^n\;a_iT){\cap}A^*$ such that a=x+y.

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