• Nonlinear Functional Analysis and Applications
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• 제26권5호
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• pp.961-969
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• 2021

In this paper, we study the ∆-convergence and strong convergence of SP-iteration scheme involving a nonexpansive mapping in partially ordered hyperbolic metric spaces. Also, we give an example to support our main result and compare SP-iteration scheme with the Mann iteration and Ishikawa iteration scheme. Thus, we generalize many previous results.

• 호남수학학술지
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• 제39권1호
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• pp.1-25
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• 2017

In this paper, we introduce a new scheme namely: CUIA-iterative scheme and utilize the same to prove a strong convergence theorem for quasi contractive mappings in Banach spaces. We also establish the equivalence of our new iterative scheme with various iterative schemes namely: Picard, Mann, Ishikawa, Agarwal et al., Noor, SP, CR etc for quasi contractive mappings besides carrying out a comparative study of rate of convergences of involve iterative schemes. The present new iterative scheme converges faster than above mentioned iterative schemes whose detailed comparison carried out with the help of different tables and graphs prepared with the help of MATLAB.

• Nonlinear Functional Analysis and Applications
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• 제26권1호
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• pp.1-11
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• 2021

In this paper we study the weak and strong convergence to minimizers of convex function of proximal point algorithm SP-iteration of three multivalued nonexpansive mappings in a Hilbert space.

• Nonlinear Functional Analysis and Applications
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• 제26권5호
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• pp.995-1009
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• 2021

Many iterative algorithms like that Picard, Mann, Ishikawa and S-iteration are very useful to elucidate the fixed point problems of a nonlinear operators in various topological spaces. The recent trend for elucidate the fixed point via inertial iterative algorithm, in which next iterative depends on more than one previous terms. The purpose of the paper is to establish convergence theorems of new inertial Picard normal S-iteration algorithm for nonexpansive mapping in Hilbert spaces. The comparison of convergence of InerNSP and InerPNSP is done with InerSP (introduced by Phon-on et al. [25]) and MSP (introduced by Suparatulatorn et al. [27]) via numerical example.

• Nonlinear Functional Analysis and Applications
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• 제27권1호
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• pp.59-82
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• 2022

In this paper, we present a modified (improved) generalized M-iteration with the inertial technique for three quasi-nonexpansive multivalued mappings in a real Hilbert space. In addition, we obtain a weak convergence result under suitable conditions and the strong convergence result is achieved using the hybrid projection method with our modified generalized M-iteration. Finally, we apply our convergence results to certain optimization problem, and present some numerical experiments to show the efficiency and applicability of the proposed method in comparison with other improved iterative methods (modified SP-iterative scheme) in the literature. The results obtained in this paper extend, generalize and improve several results in this direction.

• 대한전자공학회논문지SP
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• 제39권4호
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• pp.462-469
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• 2002

벡터 부호책 설계에 사용되는 기존 K-means 알고리즘은 모든 학습반복에서 고정된 가중치를 적용하는데 반해 제안된 방법은 학습반복마다 가변되는 가중치를 적용한다. 초기 학습반복에서는 새로운 부호벡터를 얻기 위해 수렴영역을 벗어나는 2 이상의 가중치를 사용하고, 이 값이 클수록 가변 가중치를 적용하는 학습반복을 줄임으로써 우수한 부호책을 설계할 수 있다. 초기 부호책 설계에 사용되는 미세분할 방법을 개선하기 위하여 소속 학습벡터와 대표벡터간의 오차를 줄이는 방법을 사용한다. 즉 자승오차가 최대인 대표벡터를 제외시키고 최소인 대표벡터를 미세분할함으로써 초기 부호벡터로 대체될 보다 적절한 대표벡터를 얻을 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권5호
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• pp.1649-1665
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• 2021

In view of the low accuracy of the traditional FunkSVD algorithm, and in order to improve the computational efficiency of the algorithm, this paper proposes a parallel algorithm of improved FunkSVD based on Spark (SP-FD). Using RMSProp algorithm to improve the traditional FunkSVD algorithm. The improved FunkSVD algorithm can not only solve the problem of decreased accuracy caused by iterative oscillations but also alleviate the impact of data sparseness on the accuracy of the algorithm, thereby achieving the effect of improving the accuracy of the algorithm. And using the Spark big data computing framework to realize the parallelization of the improved algorithm, to use RDD for iterative calculation, and to store calculation data in the iterative process in distributed memory to speed up the iteration. The Cartesian product operation in the improved FunkSVD algorithm is divided into blocks to realize parallel calculation, thereby improving the calculation speed of the algorithm. Experiments on three standard data sets in terms of accuracy, execution time, and speedup show that the SP-FD algorithm not only improves the recommendation accuracy, shortens the calculation interval compared to the traditional FunkSVD and several other algorithms but also shows good parallel performance in a cluster environment with multiple nodes. The analysis of experimental results shows that the SP-FD algorithm improves the accuracy and parallel computing capability of the algorithm, which is better than the traditional FunkSVD algorithm.

• 대한전자공학회논문지SP
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• 제41권3호
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• pp.73-81
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• 2004

지문영상에서 신뢰할 만한 특징을 추출하기 위한 세선화 알고리즘은 전처리 과정에 있어서 매우 중요한 부분을 차지한다. 본 논문에서 제안하는 세선화 알고리즘은 2치화된 지문영상의 연결성을 파괴하지 않고, 중심선에 가장 관접한 골격선을 최소 1화소 두께로 만들 수 있는 강건한 병렬 세선화 알고리즘을 제안하는 것이다. 제안한 기법은 3개의 부반복에 의해 반복 수행되며, 첫 번째 부반복은 내부점에 의해 최외각 경계 화소만을 제거하는 것이며, 두 번째 부반복은 2화소 두께의 골격선을 찾아 한쪽 골격선만을 추출한다. 세 번째 부반복은 골격선에 여분으로 존재하는 2화소 두께의 화소를 제거한다. 따라서 제안하는 세선화 방법은 회전과 잡음에 강건하며 균형 잡힌 중심선을 만들어낸다. 세선화 알고리즘의 성능을 평가하기 위하여 이전에 발표된 알고리즘들과 비교 분석하였다.

• Animal cells and systems
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• 제4권1호
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• pp.31-37
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• 2000

The genetic variations among six species of Rana from Korea (R. nigro-maculata, R. piancyi, R. dybowskii, R. sp, R. rugosa type A, B and R. amurensis) were investigated using 499 bases of mitochondrial DNA sequences for ND2 (NADH dehydrogenase subunit 2) gene and $tRNA^{Trp}$ gene. Partial sequences of ND2 gene (427 bp) and full sequences of $tRNA^{Trp}$ gene (73 bp) were identified. The level of sequence divergences ranged from 0.2 to 5.2% within species and 4.9-28.0% among 6 species of the genus Rana. The $tRNA^{Trp}$ gene of the genus Rana was composed of 77 nucleotides which showed a two dimensional "cloverleaf" structure. The secondary structure of $tRNA^{Trp}$ was not found compensatory changes which could potentially confound phylogenetic inference. In the neighborjoining tree, brown frogs were clustered first with the level of sequence divergence of 13.20% between R. amurensis and R. dybowskii, and 9% between R. dybowskii and R. sp. supported by 99% bootstrap iterations, respectively. R. nigromaculata and R. plancyi were clustered into another group with 5.1% divergence supported by 100% bootstrap iteration. R. rugosa A 8nd B types were grouped by 4.9% divergence and clustered into the last group with other two groups with 100% bootstrap iterations.

• 한국정보통신학회논문지
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• 제18권9호
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• pp.2087-2093
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• 2014

본 논문에서는 압축적으로 센싱된 희소 신호를 복원하기 위한 유전 알고리듬(GA)에 기반한 직교 정합 추구 방법(GAOMP)을 제안한다. 최근에 제안된 SP, CoSaMP, gOMP 등은 매 반복 단계에서 부적절한 atom을 제거하여 희소 신호의 복원 성능을 개선하였다. 그러나 support set이 국소 최저에 빠져 신호 복원에 실패하는 경우가 발생한다. 제안된 GAOMP는 유전 알고리듬의 중요 연산자인 변이를 통해 support set이 국소 최저를 벗어날 수 있도록 도와주어 희소 신호의 복원 성능을 향상시킨다. 모의 실험을 통해 GAOMP가 여러 OMP 기반 알고리듬과 $l_1$ 최적화보다 우수한 신호 복원 성능을 보임을 알 수 있다.