• Journal of applied mathematics & informatics
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• 제27권3_4호
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• pp.621-638
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• 2009

The linear system Ax = b will have (i) no solution, (ii) only one non-trivial (trivial) solution, or (iii) infinity of solutions. Our focus will be on cases (ii) and (iii). The mathematical models of many real-world problems give rise to (a) ill-conditioned linear systems, (b) singular linear systems (A is singular with all its linearly independent rows are sufficiently linearly independent), or (c) ill-conditioned singular linear systems (A is singular with some or all of its strictly linearly independent rows are near-linearly dependent). This article highlights the scope and need of a randomized algorithm for ill-conditioned/singular systems when a reasonably narrow domain of a solution vector is specified. Further, it stresses that with the increasing computing power, the importance of randomized algorithms is also increasing. It also points out that, for many optimization linear/nonlinear problems, randomized algorithms are increasingly dominating the deterministic approaches and, for some problems such as the traveling salesman problem, randomized algorithms are the only alternatives.

• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.1212-1220
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• 2015

This article presents a new nonlinear joint (state and parameter) estimation algorithm based on fusion of Kalman filter and randomized unscented Kalman filter (UKF), called Kalman randomized joint UKF (KR-JUKF). It is assumed that the measurement equation is linear. The KRJUKF is suitable for time varying and severe nonlinear dynamics and does not have any systematic error. Finally, joint-EKF, dual-EKF, joint-UKF and KR-JUKF are applied to a CSTR with cooling jacket, in which production of propylene glycol happens and performance of KR-JUKF is evaluated.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제12권1호
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• pp.227-247
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• 2018

For intermittently connected wireless sensor networks deployed in hash environments, sensor nodes may fail due to internal or external reasons at any time. In the process of data collection and recovery, we need to speed up as much as possible so that all the sensory data can be restored by accessing as few survivors as possible. In this paper a novel redundant data storage algorithm based on minimum spanning tree and quasi-randomized matrix-QRNCDS is proposed. QRNCDS disseminates k source data packets to n sensor nodes in the network (n>k) according to the minimum spanning tree traversal mechanism. Every node stores only one encoded data packet in its storage which is the XOR result of the received source data packets in accordance with the quasi-randomized matrix theory. The algorithm adopts the minimum spanning tree traversal rule to reduce the complexity of the traversal message of the source packets. In order to solve the problem that some source packets cannot be restored if the random matrix is not full column rank, the semi-randomized network coding method is used in QRNCDS. Each source node only needs to store its own source data packet, and the storage nodes choose to receive or not. In the decoding phase, Gaussian Elimination and Belief Propagation are combined to improve the probability and efficiency of data decoding. As a result, part of the source data can be recovered in the case of semi-random matrix without full column rank. The simulation results show that QRNCDS has lower energy consumption, higher data collection efficiency, higher decoding efficiency, smaller data storage redundancy and larger network fault tolerance.

• Journal of the Korean Statistical Society
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• 제23권2호
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• pp.463-482
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• 1994

In Bayesian analysis of randomized response models, the likelihood function does not combine tractably with typical priors for the parameters of interest, causing computational difficulties in posterior analysis of the parameters of interest. In this article, the difficulties are solved by introducing appropriate latent variables to the model and using the Gibbs sampling algorithm.

• Journal of Communications and Networks
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• 제10권4호
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• pp.437-443
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• 2008

The randomized projective coordinate (RPC) method applied to a pairing computation algorithm is a good solution that provides an efficient countermeasure against side channel attacks. In this study, we investigate measures for increasing the efficiency of the RPC-based countermeasures and construct a method that provides an efficient RPC-based countermeasure against side channel attacks. We then apply our method to the well-known $\eta_T$ pairing algorithm over binary fields and obtain an RPC-based countermeasure for the $\eta_T$ pairing; our method is more efficient than the RPC method applied to the original $\eta_T$ pairing algorithm.

• 대한수학회보
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• 제42권4호
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• pp.837-849
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• 2005

In this paper, we obtain a successive quadratic programming algorithm for solving the semidefinite programming (SDP) relaxation of the binary quadratic programming. Combining with a randomized method of Goemans and Williamson, it provides an efficient approximation for the binary quadratic programming. Furthermore, its convergence result is given. At last, We report some numerical examples to compare our method with the interior-point method on Maxcut problem.

• 전자공학회논문지SC
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• 제44권6호
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• pp.11-20
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• 2007

기존 Hough transform을 이용한 타원 검출의 수행 속도와 개수의 추정을 개선하기 위해 본 논문에서는 선분 세그먼트 기반 Randomized Hough Transform (RHT)을 제안한다. 제안하는 방법은 에지 영상을 선분 세그먼트 단위로 분할한 후 임의의 선분 세그먼트 쌍을 RHT를 이용해서 타원을 추정하여 병합여부를 판단한다. 이와 같이 선분 세그먼트 단위로 RHT를 적용하면 적은 반복수행으로 타원을 추정할 수 있으며 복잡한 에지 영상에서도 보다 정확한 타원의 개수를 추정할 수 있다. 제안된 방법의 효율성은 계산속도 및 타원검출의 정확도로 평가하였으며 다양한 입력영상에 대한 실험을 통해 입증하였다.

• 한국지능시스템학회논문지
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• 제15권4호
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• pp.505-510
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• 2005

제어 입력 선택 문제에 있어서 확률적 전략을 활용하는 RPO(randomized policy optimizer) 기법은 최근에 개발된 강화학습 기법으로써, 많은 적용 사례를 통해서 그 가능성이 입증되고 있다 본 논문에서는, 수정된 RPO 알고리즘을 제안하는데, 이 수정된 알고리즘의 크리틱 네트워크 부분은 RLS(recursive least square) 기법을 통하여 갱신된다. 수정된 RPO 기법의 효율성을 확인하기 위해 Kimura에 의해서 연구된 로봇에 적용하여 매우 우수한 성능을 관찰하였다. 또한, 매트랩 애니메이션 프로그램의 개발을 통해서, 로봇의 이동이 시간에 따라 가속되는 학습 알고리즘의 효과를 시각적으로 확인 할 수 있었다.

• 한국정보과학회:학술대회논문집
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• 한국정보과학회 2011년도 한국컴퓨터종합학술대회논문집 Vol.38 No.1(D)
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• pp.232-233
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• 2011

We propose a randomized distributed scheduling algorithm which can achieve the optimal throughput under the general interference model. The proposed algorithm is analyzed to show an attractive performance in that it can return a maximal schedule with high probability and has a low time-complexity. We also provide the simulation results to validate performance analysis of our algorithm.

• 정보보호학회논문지
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• 제13권5호
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• pp.169-177
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• 2003

본 논문에서는 DPA와 Goubin의 공격을 동시에 방어하도록 하는 타원곡선 스칼라 곱셈 알고리듬의 일반적인 조건을 제시하며, 제시된 조건을 만족하면 두 공격 모두를 방지할 수 있음을 보인다. 이러한 조건을 만족하는 것으로는 Ha-Moon의 재부호화 방법을 이용한 랜덤 스칼라 곱셈 알고리듬이 있음을 보이고, 또한 Ha-Moon의 재부호 방법을 변형하여 두 공격을 방지하는 새로운 재부호화 알고리듬을 제안한다. 효율성 면에서 제안하는 스칼라 곱셈 방식은 Izu-Takagi의 스칼라 곱셈방법(y-좌표를 계산하지 않고 Montgomery-ladder를 사용)과 비교될 만큼 효율적이다. 제안하는 스칼라 곱셈은 랜덤화된 사영좌표와 기저점 은닉(bsae point blinding) 또는 isogeny 함수를 결합한 방법보다 빠르다. 또한 Izu-Takagi의 경우 은닉 또는 isogeny 함수 방법을 이용하면 상당량의 시스템 파라미터를 EEPROM에 저장해야 하는 단점이 있지만 이것은 제안하는 스칼라 곱셈 방법에는 해당되지 않는다.