Search Results - (( parallel optimization model algorithm ) OR ( control function path algorithm ))
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1
Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…The proposed technique has provided through four fundamental steps, including modelling of parallel applications, meta-heuristic optimization, partitioning, and parallel job scheduling. …”
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2
Hybrid path planning for indoor robot with Laplacian Behaviour-based control via four point-explicit group
Published 2014“…Consequently, the gradient of the potential functions would be used by the searching algorithm to generate path from starting to goal location. …”
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3
Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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4
False path identification algorithm framework for nonseparable controller-data path circuits
Published 2016“…This paper proposes an algorithm frame-work to deal with these false paths through identification for DFT test. …”
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5
Nlfxlms and thf-nlfxlms algorithms for wiener-hammerstein nonlinear active noise control
Published 2016“…Filtered-X least mean square (FXLMS) control algorithm is a conventional algorithm employed to cancel the noise in linear environment. …”
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6
False path identification algorithm framework for nonseparable controller-data path circuits
Published 2017“…This paper proposes an algorithm framework to deal with these false paths through identification for DFT test. …”
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7
Nonlinear FXLMS algorithm for active noise control systems with saturation nonlinearity
Published 2012“…In active noise control (ANC) applications, the saturation effect of the loudspeaker in the secondary path is considered as the most serious problem that could degrade performance of standard filtered-x least mean square (FXLMS) control algorithm. …”
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8
Improved black-winged kite algorithm and finite element analysis for robot parallel gripper design
Published 2024“…This paper presents a comprehensive study on the design optimization of a robotic gripper, focusing on both the gripper modeling and the optimization of its parallel mechanism structure. …”
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9
Workflow optimization in distributed computing environment for stream-based data processing model / Saima Gulzar Ahmad
Published 2017“…Similarly, when data parallelism is introduced in the algorithm the performance of the algorithm improved further by 12% in latency and 17% in throughput when compared to PDWA algorithm. …”
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10
Nonlinear adaptive algorithm for active noise control with loudspeaker nonlinearity
Published 2014“…The proposed THF-NLFXLMS algorithm models the Wiener secondary path and applies the estimated degree of nonlinearity of the nonlinear secondary path in the control algorithm design. …”
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11
All-pass filtered x least mean square algorithm for narrowband active noise control
Published 2018“…Recently several new ANC algorithms have been developed; in which there is no requirement for the modelling of the secondary path transfer function. …”
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12
Reusable data-path architecture for encryption-then-authentication on FPGA
Published 2023“…Reuse of resources or identical functions however require controllers that enable sharing of data path that can also has different �rounds� of transforms required for different modes either PHOTON or LED in this case, in addition to controllers for individual algorithm. …”
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13
Development of robust control scheme for wheeled mobile robot in restricted environment
Published 2021“…A simulation study of WMR control in pre-planned paths in two environments namely, zigzag and highly curved terrains, has been conducted to verify the proposed algorithm and compare it with other existed algorithms. …”
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14
Nonlinear THF-FXLMS algorithm for active noise control with loudspeaker nonlinearity
Published 2016“…The proposed THF-NLFXLMS algorithm, models the nonlinear secondary path and applies the estimated degree of nonlinearity in the control algorithm design. …”
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15
Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…As the total objective values in most of problems could not be improved by simulated algorithm, it proved the well performing of proposed intelligence based genetic algorithm in reaching the near optimal solutions.…”
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16
Sequential and parallel multiple tabu search algorithm for multiobjective urban transit scheduling problems
Published 2018“…Additionally, the MTS algorithm is also implemented in parallel computing to produce parallel MTS for generating comparable solutions in shorter computational times. …”
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17
Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023“…Genetic algorithms are powerful optimizing techniques that are used successfully to solve problems in many different disciplines. …”
Conference paper -
18
Design and implementation of a real-time adaptive learning algorithm controller for a 3-DOF parallel manipulator / Mustafa Jabbar Hayawi
Published 2015“…Performance indices such as workspace, dexterity and stiffness, of the parallel manipulator are studied. The parallel manipulator is optimized based on the performance indices to obtain on the optimal design parameters for achieved maximum performance of the parallel manipulator. …”
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19
The performance effect due to varying network topologies on a software-defined network employing the k-shortest path
Published 2022“…K-shortest paths algorithm discovers a set of paths ordered in the most optimal, optimal, and suboptimal, has a very wide application is integrated into SDN controller to handle routing functionality. …”
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20
Parallel multiple tabu search for multiobjective Urban Transit Scheduling Problem
Published 2020“…A parallel tabu search algorithm was proposed to solve the problem by modifying the initialization process and incorporating intensification and diversification approaches to guide the search effectively from the different feasible domain in finding optimal solutions with lesser computational effort. …”
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