• 제목/요약/키워드: Fang Algorithm

검색결과 68건 처리시간 0.021초

A new swarm intelligent optimization algorithm: Pigeon Colony Algorithm (PCA)

  • Yi, Ting-Hua;Wen, Kai-Fang;Li, Hong-Nan
    • Smart Structures and Systems
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    • 제18권3호
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    • pp.425-448
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    • 2016
  • In this paper, a new Pigeon Colony Algorithm (PCA) based on the features of a pigeon colony flying is proposed for solving global numerical optimization problems. The algorithm mainly consists of the take-off process, flying process and homing process, in which the take-off process is employed to homogenize the initial values and look for the direction of the optimal solution; the flying process is designed to search for the local and global optimum and improve the global worst solution; and the homing process aims to avoid having the algorithm fall into a local optimum. The impact of parameters on the PCA solution quality is investigated in detail. There are low-dimensional functions, high-dimensional functions and systems of nonlinear equations that are used to test the global optimization ability of the PCA. Finally, comparative experiments between the PCA, standard genetic algorithm and particle swarm optimization were performed. The results showed that PCA has the best global convergence, smallest cycle indexes, and strongest stability when solving high-dimensional, multi-peak and complicated problems.

THE (R,S)-SYMMETRIC SOLUTIONS TO THE LEAST-SQUARES PROBLEM OF MATRIX EQUATION AXB = C

  • Liang, Mao-Lin;Dai, Li-Fang;Wang, San-Fu
    • Journal of applied mathematics & informatics
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    • 제27권5_6호
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    • pp.1061-1071
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    • 2009
  • For real generalized reflexive matrices R, S, i.e., $R^T$ = R, $R^2$ = I, $S^T$ = S, $S^2$ = I, we say that real matrix X is (R,S)-symmetric, if RXS = X. In this paper, an iterative algorithm is proposed to solve the least-squares problem of matrix equation AXB = C with (R,S)-symmetric X. Furthermore, the optimal approximation solution to given matrix $X_0$ is also derived by this iterative algorithm. Finally, given numerical example and its convergent curve show that this method is feasible and efficient.

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Fast Extraction of Pedestrian Candidate Windows Based on BING Algorithm

  • Zeng, Jiexian;Fang, Qi;Wu, Zhe;Fu, Xiang;Leng, Lu
    • Journal of Multimedia Information System
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    • 제6권1호
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    • pp.1-6
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    • 2019
  • In the field of industrial applications, the real-time performance of the target detection problem is very important. The most serious time consumption in the pedestrian detection process is the extraction phase of the candidate window. To accelerate the speed, in this paper, a fast extraction of pedestrian candidate window based on the BING (Binarized Normed Gradients) algorithm replaces the traditional sliding window scanning. The BING features are extracted with the positive and negative samples and input into the two-stage SVM (Support Vector Machine) classifier for training. The obtained BING template may include a pedestrian candidate window. The trained template is loaded during detection, and the extracted candidate windows are input into the classifier. The experimental results show that the proposed method can extract fewer candidate window and has a higher recall rate with more rapid speed than the traditional sliding window detection method, so the method improves the detection speed while maintaining the detection accuracy. In addition, the real-time requirement is satisfied.

Off-grid direction-of-arrival estimation for wideband noncircular sources

  • Xiaoyu Zhang;Haihong Tao;Ziye, Fang;Jian Xie
    • ETRI Journal
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    • 제45권3호
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    • pp.492-504
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    • 2023
  • Researchers have recently shown an increased interest in estimating the direction-of-arrival (DOA) of wideband noncircular sources, but existing studies have been restricted to subspace-based methods. An off-grid sparse recovery-based algorithm is proposed in this paper to improve the accuracy of existing algorithms in low signal-to-noise ratio situations. The covariance and pseudo covariance matrices can be jointly represented subject to block sparsity constraints by taking advantage of the joint sparsity between signal components and bias. Furthermore, the estimation problem is transformed into a single measurement vector problem utilizing the focused operation, resulting in a significant reduction in computational complexity. The proposed algorithm's error threshold and the Cramer-Rao bound for wideband noncircular DOA estimation are deduced in detail. The proposed algorithm's effectiveness and feasibility are demonstrated by simulation results.

중국 산학서 「대수술(代數術)」 권1(券), 권2(券)에 나타난 산법(算法)에 대한 고찰

  • 남영만
    • East Asian mathematical journal
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    • 제28권4호
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    • pp.475-485
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    • 2012
  • In this paper, we research contents of the ancient book ; Dae-su-sul (Algebra) compiled by Heng-Fang Hua(華衡芳) and translated by John Fryer(傅蘭雅). We find methods of calculation and algorithm in the first and second volume of Dae-su-sul, and investigate the influence on modern Korean mathematical development.

Least Square Channel Estimation for Two-Way Relay MIMO OFDM Systems

  • Fang, Zhaoxi;Shi, Jiong
    • ETRI Journal
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    • 제33권5호
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    • pp.806-809
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    • 2011
  • This letter considers the channel estimation for two-way relay MIMO OFDM systems. A least square (LS) channel estimation algorithm under block-based training is proposed. The mean square error (MSE) of the LS channel estimate is computed, and the optimal training sequences with respect to this MSE are derived. Some numerical examples are presented to evaluate the performance of the proposed channel estimation method.

Majorization-Minimization-Based Sparse Signal Recovery Method Using Prior Support and Amplitude Information for the Estimation of Time-varying Sparse Channels

  • Wang, Chen;Fang, Yong
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권10호
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    • pp.4835-4855
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    • 2018
  • In this paper, we study the sparse signal recovery that uses information of both support and amplitude of the sparse signal. A convergent iterative algorithm for sparse signal recovery is developed using Majorization-Minimization-based Non-convex Optimization (MM-NcO). Furthermore, it is shown that, typically, the sparse signals that are recovered using the proposed iterative algorithm are not globally optimal and the performance of the iterative algorithm depends on the initial point. Therefore, a modified MM-NcO-based iterative algorithm is developed that uses prior information of both support and amplitude of the sparse signal to enhance recovery performance. Finally, the modified MM-NcO-based iterative algorithm is used to estimate the time-varying sparse wireless channels with temporal correlation. The numerical results show that the new algorithm performs better than related algorithms.

조선시대의 산학서 <구일집>의 내용 분석 및 교육적 활용 방안 탐구 (Analysis on Gu-il-jip, the mathematical book of Chosun dynasty and its pedagogical applications)

  • 장혜원
    • 대한수학교육학회지:수학교육학연구
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    • 제13권4호
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    • pp.429-446
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    • 2003
  • <구일집>은 9장으로 이루어진 조선 후기의 대표적인 산학서이다. 473개 이상의 문제와 그에 대한 풀이가 주를 이루는 이 책의 내용을 분석함으로써 당시의 전문 산학 자에 의한 수학적 활동을 음미할 수 있다 그 중, 측정 단위와 소수 표기, 원주율 및 원의 넓이와 구의 부피, 거듭제곱 명명법, 계산 도구인 산대의 이용, 남거나 모자라는 양에 대한 계산법인 영부족술, 연립방정식의 해법인 방정술, 다항식의 표기법인 천원술, 고차방정식의 해법인 개방술 등은 오늘날의 수학 지식 및 방법과 비교할 때 특히 주목할 만하다. 이러한 분석에 기초하여 학교 수학에서의 교육적 활용 가능성을 타진해 본다.

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Improved AP Deployment Optimization Scheme Based on Multi-objective Particle Swarm Optimization Algorithm

  • Kong, Zhengyu;Wu, Duanpo;Jin, Xinyu;Cen, Shuwei;Dong, Fang
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제15권4호
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    • pp.1568-1589
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    • 2021
  • Deployment of access point (AP) is a problem that must be considered in network planning. However, this problem is usually a NP-hard problem which is difficult to directly reach optimal solution. Thus, improved AP deployment optimization scheme based on swarm intelligence algorithm is proposed to research on this problem. First, the scheme estimates the number of APs. Second, the multi-objective particle swarm optimization (MOPSO) algorithm is used to optimize the location and transmit power of APs. Finally, the greedy algorithm is used to remove the redundant APs. Comparing with multi-objective whale swarm optimization algorithm (MOWOA), particle swarm optimization (PSO) and grey wolf optimization (GWO), the proposed deployment scheme can reduce AP's transmit power and improves energy efficiency under different numbers of users. From the experimental results, the proposed deployment scheme can reduce transmit power about 2%-7% and increase energy efficiency about 2%-25%, comparing with MOWOA. In addition, the proposed deployment scheme can reduce transmit power at most 50% and increase energy efficiency at most 200%, comparing with PSO and GWO.

고품질 바이그램을 이용한 문서 범주화 성능 향상 (Improving Text Categorization with High Quality Bigrams)

  • 이찬도;탄체이드멩;왕유안팡
    • 정보처리학회논문지B
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    • 제9B권4호
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    • pp.415-420
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    • 2002
  • 본 논문은 정보이익을 사용하여 고품질 바이그램을 생성하는 효율적 문서 범주화 알고리즘을 제안한다. 실험 결과 유니그램에 적은 수의 바이그램을 추가해서 나이브 베이즈 분류기에 적용했을 때 문서 범주화 성공률은 상당히 향상되었다. 결과 분석은 제안한 알고리즘이 양의 문서를 분류하는데 더 우수하다는 것을 제시한다.