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Relevant bibliographies by topics / Maximum Subarray Problem

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Academic literature on the topic 'Maximum Subarray Problem'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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Journal articles on the topic "Maximum Subarray Problem"

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Rojek, Tomasz. "MAXIMUM SUBARRAY PROBLEM OPTIMIZATION FOR SPECIFIC DATA." Informatics Control Measurement in Economy and Environment Protection 7, no. 4 (2017): 62–65. http://dx.doi.org/10.5604/01.3001.0010.7507.

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The maximum subarray problem (MSP) is to the find maximum contiguous sum in an array. This paper describes a method of Kadanes algorithm (the state of the art) optimization for specific data (continuous sequences of zeros or negative real numbers). When the data are unfavourable, the modification of the algorithm causes a non significant performance loss (1% > decrease in performance). The modification does not improve time complexity but reduces the number of elementary operations. Various experimental data sets have been used to evaluate possible time efficiency improvement. For the most

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Bae, S. E. "Improved Algorithms for the K-Maximum Subarray Problem." Computer Journal 49, no. 3 (2005): 358–74. http://dx.doi.org/10.1093/comjnl/bxl007.

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TAMAKI, Hisao, and Takeshi TOKUYAMA. "Algorithms for the Maximum Subarray Problem Based on Matrix Multiplication." Interdisciplinary Information Sciences 6, no. 2 (2000): 99–104. http://dx.doi.org/10.4036/iis.2000.99.

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BAE, SUNG EUN, and TADAO TAKAOKA. "ALGORITHMS FOR K-DISJOINT MAXIMUM SUBARRAYS." International Journal of Foundations of Computer Science 18, no. 02 (2007): 319–39. http://dx.doi.org/10.1142/s012905410700470x.

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The maximum subarray problem is to find the array portion that maximizes the sum of array elements in it. For K disjoint maximum subarrays, Ruzzo and Tompa gave an O(n) time solution for one-dimension. This solution is, however, difficult to extend to two-dimensions. While a trivial solution of O(Kn3) time is easily obtainable for a two-dimensional array of size n × n, little study has been undertaken to improve the time complexity. We first propose an O(n + K log K) time solution for one-dimension. This is asymptotically equivalent to Ruzzo and Tompa's when sorted order is needed. Based on th

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Takaoka, Tadao. "Efficient Algorithms for the Maximum Subarray Problem by Distance Matrix Multiplication." Electronic Notes in Theoretical Computer Science 61 (January 2002): 191–200. http://dx.doi.org/10.1016/s1571-0661(04)00313-5.

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Yang, Kaikai, Sheng Hong, Qi Zhu, and Yanheng Ye. "Maximum Likelihood Angle-Range Estimation for Monostatic FDA-MIMO Radar with Extended Range Ambiguity Using Subarrays." International Journal of Antennas and Propagation 2020 (September 8, 2020): 1–10. http://dx.doi.org/10.1155/2020/4601208.

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In this paper, we consider the joint angle-range estimation in monostatic FDA-MIMO radar. The transmit subarrays are first utilized to expand the range ambiguity, and the maximum likelihood estimation (MLE) algorithm is first proposed to improve the estimation performance. The range ambiguity is a serious problem in monostatic FDA-MIMO radar, which can reduce the detection range of targets. To extend the unambiguous range, we propose to divide the transmitting array into subarrays. Then, within the unambiguous range, the maximum likelihood (ML) algorithm is proposed to estimate the angle and r

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Ren, Jia, Kun Liu, Yani Cui, and Wencai Du. "Search Path Planning Algorithm Based on the Probability of Containment Model." Mathematical Problems in Engineering 2021 (January 28, 2021): 1–12. http://dx.doi.org/10.1155/2021/7459239.

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The location of distress object in the maritime search area is difficult to determine, which has brought great difficulties to the search path planning. Aiming at this problem, a search path planning algorithm based on the probability of containment (POC) model for a distress object is proposed. This algorithm divides the area to be searched into several subareas by grid method and dynamically evaluates the POC of the distress object in each subarea using the Monte Carlo random particle method to build the POC model. On this basis, the POC is dynamically updated by employing the Bayes criterio

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Jiang, Zhongtai, Dexin Yu, Huxing Zhou, Siliang Luan, and Xue Xing. "A Trajectory Optimization Strategy for Connected and Automated Vehicles at Junction of Freeway and Urban Road." Sustainability 13, no. 17 (2021): 9933. http://dx.doi.org/10.3390/su13179933.

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The phenomenon of stop-and-go traffic and its environmental impact has become a crucial issue that needs to be tackled, in terms of the junctions between freeway and urban road networks, which consist of freeway off-ramps, downstream intersections, and the junction section. The development of Connected and Automated Vehicles (CAVs) has provided promising solutions to tackle the difficulties that arise along intersections and freeway off-ramps separately. However, several problems still exist that need to be handled in terms of junction structure, including vehicle merging trajectory optimizati

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Lichev, Lyuben. "A Note on the Erdős-Szekeres Theorem in Two Dimensions." Electronic Journal of Combinatorics 28, no. 2 (2021). http://dx.doi.org/10.37236/9880.

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Burkill and Mirsky, and Kalmanson prove independently that, for every $r\ge 2, n\ge 1$, there is a sequence of $r^{2^n}$ vectors in $\mathbb R^n$, which does not contain a subsequence of $r+1$ vectors $v^1, v^2,\dots,v^{r+1}$ such that, for every $i$ between 1 and $n$, $(v^{j}_i)_{1\le j\le r+1}$ forms a monotone sequence. Moreover, $r^{2^n}$ is the largest integer with this property. In this short note, for two vectors $u = (u_1, u_2,\dots, u_n)$ and $v = (v_1, v_2, \dots, v_n)$ in $\mathbb{R}^n$, we say that $u\le v$ if, for every $i$ between 1 and $n$, $u_i\le v_i$. Just like Burkill and Mi

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Silva Junior, Marcos Antonio Barbosa da, Simone Rosa da Silva, and Jaime Joaquim da Silva Pereira Cabral. "Compensatory alternatives for flooding control in urban areas with tidal influence in Recife - PE." RBRH 22 (2017). http://dx.doi.org/10.1590/2318-0331.011716040.

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ABSTRACT This paper presents a study of compensatory alternatives in urban drainage, using SWMM model (Storm Water Management Model), for the critical point of flooding in an urban area and vulnerable to tide fluctuations, located in Recife. For this, we used the registered information of the micro-drainage network and defined the parameters and variables required for modeling, such as: the subareas of contribution to the drainage system, indicating the percentage of soil waterproofing, equivalent width, slope, and infiltration rate; project rain; and tide curve. Two alternatives were simulate

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Dissertations / Theses on the topic "Maximum Subarray Problem"

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Lee, Sang Myung (Chris). "Sub-cubic Time Algorithm for the k-disjoint Maximum subarray Problem." Thesis, University of Canterbury. Computer Science and Software Engineering, 2011. http://hdl.handle.net/10092/6494.

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The maximum subarray problem is to find the array portion that maximizes the sum of array elements in it. This problem was first introduced by Grenander and brought to computer science by Bentley in 1984. This problem has been branched out into other problems based on their characteristics. k-overlapping maximum subarray problem where the overlapping solutions are allowed, and k-disjoint maximum subarray problem where all the solutions are disjoint from each other are those. For k-overlapping maximum subarray problems, significant improvement have been made since the problem was first introduc

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Bae, Sung Eun. "Sequential and Parallel Algorithms for the Generalized Maximum Subarray Problem." Thesis, University of Canterbury. Computer Science and Software Engineering, 2007. http://hdl.handle.net/10092/1202.

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The maximum subarray problem (MSP) involves selection of a segment of consecutive array elements that has the largest possible sum over all other segments in a given array. The efficient algorithms for the MSP and related problems are expected to contribute to various applications in genomic sequence analysis, data mining or in computer vision etc. The MSP is a conceptually simple problem, and several linear time optimal algorithms for 1D version of the problem are already known. For 2D version, the currently known upper bounds are cubic or near-cubic time. For the wider applications, it would

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Bashar, Mohammad Ehsanul. "Average case analysis of algorithms for the maximum subarray problem." Thesis, University of Canterbury. Computer Science and Software Engineering, 2007. http://hdl.handle.net/10092/1194.

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Maximum Subarray Problem (MSP) is to find the consecutive array portion that maximizes the sum of array elements in it. The goal is to locate the most useful and informative array segment that associates two parameters involved in data in a 2D array. It's an efficient data mining method which gives us an accurate pattern or trend of data with respect to some associated parameters. Distance Matrix Multiplication (DMM) is at the core of MSP. Also DMM and MSP have the worst-case complexity of the same order. So if we improve the algorithm for DMM that would also trigger the improvement of MSP. Th

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Bashar, Mohammad. "Average case analysis of algorithms for the maximum subarray problem : a thesis submitted in partial fulfilment of the requirements for the degree of Master of Science in Computer Science in the University of Canterbury /." 2007. http://library.canterbury.ac.nz/etd/adt-NZCU20071024.010106.

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Lin, Rung-Ren. "Algorithms for finding the maximum-density path and maximum subarray problems." 2004. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0001-0707200417245400.

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Lin, Rung-Ren, and 林容任. "Algorithms for finding the maximum-density path and maximum subarray problems." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/53796339105555842330.

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碩士<br>國立臺灣大學<br>資訊工程學研究所<br>92<br>We propose some algorithms to solve two problems in this thesis. The first problem is to find a length-constrained maximum-density path in a tree. Given a tree with n edges, we present two efficient algorithm for finding a maximum-density path of length at least L in O(nL) time. One of them is further modified to solve full m-ary trees in O(n) time. The other problem is to find the maximum subarray in a two-dimensional array. Given an m×n array of numbers, we develop two heuristic algorithms for computing the maximum subarray in O(nm + km^2), where k is a give

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Book chapters on the topic "Maximum Subarray Problem"

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Bae, Sung E., and Tadao Takaoka. "Improved Algorithms for the K-Maximum Subarray Problem for Small K." In Lecture Notes in Computer Science. Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11533719_63.

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Lima, Anderson C., Rodrigo G. Branco, and Edson N. Cáceres. "Efficient BSP/CGM Algorithms for the Maximum Subarray Sum and Related Problems." In Computational Science and Its Applications -- ICCSA 2015. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-21404-7_29.

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Conference papers on the topic "Maximum Subarray Problem"

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Saleh, Salah, Marwan Abdellah, Ahmed A. Abdel Raouf, and Yasser M. Kadah. "High performance CUDA-based implementation for the 2D version of the Maximum Subarray Problem (MSP)." In 2012 Cairo International Biomedical Engineering Conference (CIBEC). IEEE, 2012. http://dx.doi.org/10.1109/cibec.2012.6473291.

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Sung Eun Bae and Tadao Takaoka. "Algorithms for the problem of K maximum sums and a VLSI algorithm for the K maximum subarrays problem." In 7th International Symposium on Parallel Architectures, Algorithms and Networks, 2004. Proceedings. IEEE, 2004. http://dx.doi.org/10.1109/ispan.2004.1300488.

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