• 제목/요약/키워드: weighted algorithm

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Community Discovery in Weighted Networks Based on the Similarity of Common Neighbors

  • Liu, Miaomiao;Guo, Jingfeng;Chen, Jing
    • Journal of Information Processing Systems
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    • 제15권5호
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    • pp.1055-1067
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    • 2019
  • In view of the deficiencies of existing weighted similarity indexes, a hierarchical clustering method initialize-expand-merge (IEM) is proposed based on the similarity of common neighbors for community discovery in weighted networks. Firstly, the similarity of the node pair is defined based on the attributes of their common neighbors. Secondly, the most closely related nodes are fast clustered according to their similarity to form initial communities and expand the communities. Finally, communities are merged through maximizing the modularity so as to optimize division results. Experiments are carried out on many weighted networks, which have verified the effectiveness of the proposed algorithm. And results show that IEM is superior to weighted common neighbor (CN), weighted Adamic-Adar (AA) and weighted resources allocation (RA) when using the weighted modularity as evaluation index. Moreover, the proposed algorithm can achieve more reasonable community division for weighted networks compared with cluster-recluster-merge-algorithm (CRMA) algorithm.

Weighted Carlson Mean of Positive Definite Matrices

  • Lee, Hosoo
    • Kyungpook Mathematical Journal
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    • 제53권3호
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    • pp.479-495
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    • 2013
  • Taking the weighted geometric mean [11] on the cone of positive definite matrix, we propose an iterative mean algorithm involving weighted arithmetic and geometric means of $n$-positive definite matrices which is a weighted version of Carlson mean presented by Lee and Lim [13]. We show that each sequence of the weigthed Carlson iterative mean algorithm has a common limit and the common limit of satisfies weighted multidimensional versions of all properties like permutation symmetry, concavity, monotonicity, homogeneity, congruence invariancy, duality, mean inequalities.

DMA Priority selection module 설계 및 구현 (Design and Implementation of DMA priority section module)

  • 황인기
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2002년도 합동 추계학술대회 논문집 정보 및 제어부문
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    • pp.264-267
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    • 2002
  • This paper proposed a effective priority selection algorithm named weighted round-robin algorithm and show the implementation result of DMAC priority selection module using prosed weighted round-robin algorithm. I parameterize timing constraints of each functional module, which decide the effectiveness of system. Proposed weighted round-robin algorithm decide the most effective module for data transmission using parameterize timing constraints and update timing parameter of each module for next transmission module selection. I implement DMAC priority selection module using this weighted round-robin algorithm and can improve the timing effective for data transmission from memory to functional module or one functional module to another functional module.

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무선통신망의 최대 가중치 독립집합 문제에 관한 분산형 알고리즘 (Distributed Algorithm for Maximal Weighted Independent Set Problem in Wireless Network)

  • 이상운
    • 한국인터넷방송통신학회논문지
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    • 제19권5호
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    • pp.73-78
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    • 2019
  • 본 논문은 NP-난제로 널리 알려진 최대 가중치 독립집합 문제에 대해 다항시간으로 풀 수 있는 규칙을 제시하였다. 기존에 알려진 분산형 알고리즘은 지역에서 최대 가중치 노드를 독립집합 원소로 결정하는 방법을 적용하였다. 그러나 지역에서 최대 가중치를 갖는 노드 단독이 아닌 보다 작은 가중치들을 갖는 노드들이 병합된 독립집합이 최대 가중치를 갖는 경우가 보다 빈번히 발생하여 기존에 알려진 방법으로는 최적 해를 구하지 못할 수도 있다. 이러한 문제점을 해결하기 위해, 본 논문에서는 지역에서 최대 가중치를 갖는 독립집합을 형성하는 방법을 제안하였다. 제안된 알고리즘을 다양한 망들에 적용한 결과, 기존에 알려진 알고리즘으로 구하지 못한 최적 해를 구할 수 있었다.

비트 레벨 정렬 알고리즘을 이용한 3${\times}$3 윈도우 가중 메디언 필터의 하드웨어 구현에 관한 연구 (A Study on the Hardware Implementation of A 3${\times}$3 Window Weighted Median Filter Using Bit-Level Sorting Algorithm)

  • 이태욱;조상복
    • 대한전기학회논문지:시스템및제어부문D
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    • 제53권3호
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    • pp.197-205
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    • 2004
  • In this paper, we studied on the hardware implementation of a 3${\times}$3 window weighted median filter using bit-level sorting algorithm. The weighted median filter is a generalization of the median filter that is able to preserve :,harp changes in signal and is very effective in removing impulse noise. It has been successfully applied in various areas such as digital signal and video/image processing. The weighted median filters are, for the most part, based on word-level sorting methods, which have more hardware and time complexity, However, the proposed bit-serial sorting algorithm uses weighted adder tree to overcome those disadvantages. It also offers a simple pipelined filter architecture that is highly regular with repeated modules and is very suitable for weighted median filtering. The algorithm was implemented by VHDL and graphical environment in MAX+PlusII of ALTERA. The simulation results indicate that the proposed design method is more efficient than the traditional ones.

Weighted Wide Vector Correlation에 근거한 Deinterlacing Algorithm (A Deinterlacing Algorithm Based on Weighted Wide Vector Correlations Signal Processing Lab., Samsung Electronics Co., Suwon)

  • 김영택;김대종
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 1995년도 학술대회
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    • pp.87-90
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    • 1995
  • In this paper, we propose a new deinterlacing algorithm based on weighted wide vector correlations. This algorithm is developed mainly for the format conversion problem encountered in current HDTV system, but not limited to. By having wide vector correlations, visually annoying artifacts caused by interlacing, such as a serrate line, line crawling, a line flicker, and a large area flicker, can be remarkably reduced, since the use of wide vector correlation increases the detectability of edges in various orientations.

SPEECH ENHANCEMENT BY FREQUENCY-WEIGHTED BLOCK LMS ALGORITHM

  • Cho, D.H.
    • 한국음향학회:학술대회논문집
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    • 한국음향학회 1985년도 학술발표회 논문집
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    • pp.87-94
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    • 1985
  • In this paper, enhancement of speech corrupted by additive white or colored noise is stuided. The nuconstrained frequency-domain block least-mean-square (UFBLMS) adaptation algorithm and its frequency-weighted version are newly applied to speech enhancement. For enhancement of speech degraded by white noise, the performance of the UFBLMS algorithm is superior to the spectral subtraction method or Wiener filtering technique by more than 3 dB in segmented frequency-weighted signal-to-noise ratio(FWSNERSEG) when SNR of speech is in the range of 0 to 10 dB. As for enhancement of noisy speech corrupted by colored noise, the UFBLMS algorithm is superior to that of the spectral subtraction method by about 3 to 5 dB in FWSNRSEG. Also, it yields better performance by about 2 dB in FWSNR and FWSNRSEG than that of time-domain least-mean-square (TLMS) adaptive prediction filter(APF). In view of the computational complexity and performance improvement in speech quality and intelligibility, the frequency-weighted UFBLMS algorithm appears to yield the best performance among various algorithms in enhancing noisy speech corrupted by white or colored noise.

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적응 FWLS 알고리즘을 응용한 시변 비선형 시스템 식별 (Utilization of the Filtered Weighted Least Squares Algorithm For the Adaptive Identification of Time-Varying Nonlinear Systems)

  • 안규영;이인환;남상원
    • 대한전기학회논문지:시스템및제어부문D
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    • 제53권12호
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    • pp.793-798
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    • 2004
  • In this paper, the problem of adaptively identifying time-varying nonlinear systems is considered. For that purpose, the discrete time-varying Volterra series is employed as a system model, and the filtered weighted least squares (FWLS) algorithm, developed for adaptive identification of linear time-varying systems, is utilized for the adaptive identification of time-varying quadratic Volterra systems. To demonstrate the performance of the proposed approach, some simulation results are provided. Note that the FWLS algorithm, decomposing the conventional weighted basis function (WBF) algorithm into a cascade of two (i.e., estimation and filtering) procedures, leads to fast parameter tracking with low computational burden, and the proposed approach can be easily extended to the adaptive identification of time-varying higher-order Volterra systems.

Nearest-Neighbors Based Weighted Method for the BOVW Applied to Image Classification

  • Xu, Mengxi;Sun, Quansen;Lu, Yingshu;Shen, Chenming
    • Journal of Electrical Engineering and Technology
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    • 제10권4호
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    • pp.1877-1885
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    • 2015
  • This paper presents a new Nearest-Neighbors based weighted representation for images and weighted K-Nearest-Neighbors (WKNN) classifier to improve the precision of image classification using the Bag of Visual Words (BOVW) based models. Scale-invariant feature transform (SIFT) features are firstly extracted from images. Then, the K-means++ algorithm is adopted in place of the conventional K-means algorithm to generate a more effective visual dictionary. Furthermore, the histogram of visual words becomes more expressive by utilizing the proposed weighted vector quantization (WVQ). Finally, WKNN classifier is applied to enhance the properties of the classification task between images in which similar levels of background noise are present. Average precision and absolute change degree are calculated to assess the classification performance and the stability of K-means++ algorithm, respectively. Experimental results on three diverse datasets: Caltech-101, Caltech-256 and PASCAL VOC 2011 show that the proposed WVQ method and WKNN method further improve the performance of classification.

글로벌 라우팅 유전자 알고리즘의 설계와 구현 (Design and Implementation of a Genetic Algorithm for Global Routing)

  • 송호정;송기용
    • 융합신호처리학회논문지
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    • 제3권2호
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    • pp.89-95
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    • 2002
  • 글로벌 라우팅(global routing)은 VLSI 설계 과정중의 하나로, 네트리스트의 모든 네트들을 연결하기 위하여 각 네트들을 라우팅 영역(routing area)에 할당시키는 문제이며, 글로벌 라우팅에서 최적의 해를 얻기 위해 maze routing 알고리즘, line-probe 알고리즘, shortest path 기반 알고리즘, Steiner tree 기반 알고리즘등이 이용된다. 본 논문에서는 라우팅 그래프에서 최단 경로 Steiner tree 탐색방법인 weighted network heuristic(WNH)과 이를 기반으로 하는 글로벌 라우팅 유전자 알고리즘(genetic algorithm; GA)을 제안하였으며, 제안한 방식을 시뮬레이티드 어닐링(SA) 방식과 비교, 분석하였다.

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