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Time complexity of algorithms
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This paper aims to develop a effective algorithm for computing geodesics on large, complex models with fast processing times to facilitate interactive applications. Our contribution is developing of the parallel window propagation (PWP) algorithm, which divides the sequential MMP algorithm into four phases: front node selection, window list propagation, window list merging, and vertex update.
6p
vigojek
02-02-2024
1
0
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Ebook "Complexity of Algorithms" contains 14 chapters, includes: Chapter 0 introduction and preliminaries, chapter 1 models of computation, chapter 2 algorithmic decidability, chapter 3 computation with resource bounds, chapter 4 general theorems on space and time complexity, chapter 5 non-deterministic algorithms, chapter 6 randomized algorithms, chapter 7 information complexity: the complexity-theoretic notion of randomness, chapter 8 pseudo-random numbers, chapter 9 parallel algorithms, chapter 10 decision trees, chapter 11 communication complexity, chapter 12 the complexity of algebraic...
180p
haojiubujain08
01-11-2023
6
2
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Part 1 of ebook "Python cookbook (Third edition)" provides readers with contents including: chapter 1 - data structures and algorithms; chapter 2 - strings and text; chapter 3 - numbers, dates, and times; chapter 4 - iterators and generators; chapter 5 - files and I/O; chapter 6 - data encoding and processing; chapter 7 - functions; chapter 8 - classes and objects;...
346p
hanlinhchi
29-08-2023
14
6
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Part 1 book "Multicriteria scheduling" includes content: Introduction to scheduling, complexity of problems and algorithms, multicriteria optimisation theory, an approach to multicriteria scheduling problems, just-in-time scheduling problems.
203p
oursky01
24-07-2023
7
5
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Advanced Algorithms Analysis and Design - Lecture 10: Time complexity of algorithms. In this lecture we will cover the following: major factors in algorithms design; complexity analysis; growth of functions; asymptotic notations; usefulness of notations; various examples explaining each concept;...
37p
andromedashun
26-05-2022
10
1
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Advanced Algorithms Analysis and Design - Lecture 26: Huffman coding. In this lecture we will cover the following: huffman problem; problem analysis; algorithm of huffman coding problem; time complexity; road trip problem; analysis and greedy algorithm;...
26p
andromedashun
26-05-2022
9
1
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Advanced Algorithms Analysis and Design - Lecture 39: Number theoretic algorithms (Theorems and algorithms). In this lecture we will cover the following: some more proofs; GCD as a linear combination; finding GCD, a recursive theorem; Euclid’s algorithm; extended Euclid’s algorithm; time complexity of Euclid’s algorithm;...
36p
andromedashun
26-05-2022
16
1
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Theory of Computation: Lecture 22. The main topics covered in this lesson include: non-deterministic time; the class P; the class NP; time complexity classes; time deterministic single tape TM; polynomial time algorithm; adjacency matrix; adjacency list; non-deterministic analog;...
40p
andromedashun
26-05-2022
6
1
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Theory of Computation: Lecture 34. The main topics covered in this lesson include: three versions of the TSP problem; an approximation algorithm for the TSP problem; space complexity; polynomial time algorithm; the euclidean TSP;...
33p
andromedashun
26-05-2022
9
1
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Theory of Computation: Lecture 41. The main topics covered in this lesson include: space complexity; generalized geography; polynomial time algorithm; algorithm requires polynomial space; the existentially quantified variables; the universally quantified variables;...
30p
andromedashun
26-05-2022
43
1
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The following will be discussed in this chapter: Complexity Theory, Decision Problems, Complexity Classes, Polynomial Time Verification, The Class NP, Reductions, Polynomial Time Reduction, NP-Completeness, Boolean Satisfiability Problem: Cook’s Theorem.
35p
youzhangjing_1909
28-04-2022
7
1
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The complete University of East Anglia repository, obtaining highly interpretable results capable of explaining the relationships between the features that compose the time series and achieving performance results statistically indistinguishable from the best algorithms of the state-of-the-art.
19p
guernsey
28-12-2021
11
1
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It is impossible to find an optimal algorithm that can reduce time and memory complexities with best detection performance. These aspects are always in conflict with each other. Thus, in each chapter, we will propose algorithms to solve each problem quite independently.
26p
larachdumlanat129
20-01-2021
30
4
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The maximal sensitivity for local alignments makes the Smith-Waterman algorithm a popular choice for protein sequence database search based on pairwise alignment. However, the algorithm is compute-intensive due to a quadratic time complexity. Corresponding runtimes are further compounded by the rapid growth of sequence databases.
10p
viwyoming2711
16-12-2020
17
0
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The Smith-Waterman algorithm is known to be a more sensitive approach than heuristic algorithms for local sequence alignment algorithms. Despite its sensitivity, a greater time complexity associated with the Smith-Waterman algorithm prevents its application to the all-pairs comparisons of base sequences, which aids in the construction of accurate phylogenetic trees.
15p
vikentucky2711
24-11-2020
6
1
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Long non-coding RNAs play an important role in human complex diseases. Identification of lncRNAdisease associations will gain insight into disease-related lncRNAs and benefit disease diagnoses and treatment. However, using experiments to explore the lncRNA-disease associations is expensive and time consuming.
12p
vicoachella2711
27-10-2020
6
0
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This work deals with the control design and development of an automated car-following strategy that further increases robustness to vehicle dynamics uncertainties. The control algorithm is applied on a hierarchical architecture where high and low level control layers are designed for gap-control and desired acceleration tracking, respectively. A fractional-order controller is proposed due to its flexible frequency shape, fulfilling more demanding design requirements.
9p
dayhoctainha
10-09-2020
20
1
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An optimization-simulation strategy has been applied by coupling a commercial process simulator (Aspen HYSYS ) with a programming tool (MATLAB ) to produce a precise steady state simulationbased optimization of a whole green-field saturated gas plant as a real case study. The plant has more than 100-components and comprises interacting three-phase fractionation towers, pumps, compressors and exchangers. The literature predominantly uses this coupling to optimize individual units at small scales, while paying more attention to optimizing discrete design decisions.
13p
partimesinhvien
08-05-2020
19
0
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Compressed sensing enables the acquisition of sparse signals at a rate that is much lower than the Nyquist rate. Compressed sensing initially adopted ‘1 minimization for signal reconstruction which is computationally expensive. Several greedy recovery algorithms have been recently proposed for signal reconstruction at a lower computational complexity compared to the optimal ‘1 minimization, while maintaining a good reconstruction accuracy. In this paper, the Reduced-set Matching Pursuit (RMP) greedy recovery algorithm is proposed for compressed sensing.
11p
kequaidan1
16-11-2019
19
0
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Circularly symmetric two-dimensional (2D) finite impulse response (FIR) filters find extensive use in image and medical applications, especially for isotropic filtering. Moreover, the design and implementation of 2D digital filters with variable fractional delay and variable magnitude responses without redesigning the filter has become a crucial topic of interest due to its significance in low-cost applications. Recently the design using fixed word length coefficients has gained importance due to the replacement of multipliers by shifters and adders, which reduces the hardware complexity.
12p
kequaidan1
16-11-2019
21
1
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