Membrane algorithms are a new class of heuristic algorithms, which attempt to incorporate some components of membrane computing models (also called P systems) for designing efficient optimization algorithms, such as t...
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Membrane algorithms are a new class of heuristic algorithms, which attempt to incorporate some components of membrane computing models (also called P systems) for designing efficient optimization algorithms, such as the structure of P systems, the way of communication between cells, etc. Membrane algorithms are a kind of parallel methods, where many operations can be performed in parallel. Although the importance of the parallelism of such algorithms is recognized, membrane algorithms were often implemented on the serial computing device Central processing Unit (CPU), which makes the algorithms cannot work in a more efficient way. In this work, we consider the implementation of membrane algorithms on the parallel computing device Graphics processing Unit (GPU). Under such implementation, all cells of membrane algorithms can work simultaneously. Experiment results on two classical intractable problems, point set matching problem and TSP, show that GPU implementation of membrane algorithms is much more efficient than CPU implementation in terms of runtime, especially for solving the problems with a high complexity.
This letter presents the graphic processor unit (GPU)implementation of the finite-difference time-domain (FDTD)method for the solution of the two-dimensional electromagnetic fields inside dispersive *** improved Z-tra...
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This letter presents the graphic processor unit (GPU)implementation of the finite-difference time-domain (FDTD)method for the solution of the two-dimensional electromagnetic fields inside dispersive *** improved Z-transform-based finite-difference time-domain (ZTFDTD) method was presented for simulating the interaction of electromagnetic wave with unmagnetized *** using the newly introduced Compute Unified Device Architecture (CUDA) technology, we illustrate the efficacy of GPU in accelerating the FDTD computations by achieving significant speedups with great ease and at no extra hardware *** effect of the GPU-CPU memory transfers on the speedup will be also studied.
The essence of maneuvering target tracking is mainly including maneuvering target modeling, maneuvering target detection or maneuvering target identification and filtering algorithm. In this paper, the maneuvering tar...
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The essence of maneuvering target tracking is mainly including maneuvering target modeling, maneuvering target detection or maneuvering target identification and filtering algorithm. In this paper, the maneuvering target model was described by the cooperative turn model, and tracked by the particle filter algorithm. The resample technique is introduced to overcome the problem of particle degradation in standard particle filter. Finally, we finished simulation experiments by Matlab, and compared the particle filter algorithm with the extended kalman filter algorithm, the results show that particle filter with the resample technique has a better performance in tracking precision, computational complexity, real-time performance and stability, it is a more effective method for maneuvering target tracking.
Particle filter is well suited to estimate the state of non-linear non-Gaussian dynamic systems,which comes at the cost of higher computational *** in many real time applications,it must deal with constraints imposed ...
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Particle filter is well suited to estimate the state of non-linear non-Gaussian dynamic systems,which comes at the cost of higher computational *** in many real time applications,it must deal with constraints imposed by limited computational *** deal with this question,we distribute the samples among the different observations arriving during a filter update, the novel algorithm represents densities over the state space by mixtures of sample *** contribution of this paper is to increasing the efficiency of particle filters by adapting the size of sample sets during the estimation *** to the relative entropy theory and particle number controller idea,we choose the number of samples,decrease computation overhead.A simulation of the classic HARD bearing only tracking problem is presented,the results show that the novel algorithm performs better than generic particle filter.
In this paper, we propose a novel model of three points named TP for location estimation in wireless sensor networks(WSNs) with random deployment of anchor nodes. In this model, we select three anchor nodes which have...
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In this paper, we propose a novel model of three points named TP for location estimation in wireless sensor networks(WSNs) with random deployment of anchor nodes. In this model, we select three anchor nodes which have the strongest received signal strength(RSS) for location estimation, the centroid algorithm and the method of intersection of judgment are used to estimate the location of unknown nodes. To further exploit three nearest intersection points in TP, the enhanced TP(ETP) is proposed. The simulation results show that the proposed models outperform MMSE and BML in terms of the localization accuracy for WSNs. Moreover, the localization accuracy of the proposed models in scenario 2 with random deployment of anchor nodes are better than in scenario 1 with planned deployment of anchor nodes. Additionally, compared with MMSE and BML, ETP and TP can reduce the environmental impact on location estimation.
Nitrogen is a key factor for plant photosynthesis, ecosystem productivity and leaf respiration. Under the condition of nitrogen deficiency, the crop shows the nitrogen deficiency symptoms in the bottom leaves, while e...
Nitrogen is a key factor for plant photosynthesis, ecosystem productivity and leaf respiration. Under the condition of nitrogen deficiency, the crop shows the nitrogen deficiency symptoms in the bottom leaves, while excessive nitrogen will affect the upper layer leaves first. Thus, timely measurement of vertical distribution of foliage nitrogen content is critical for growth diagnosis, crop management and reducing environmental impact. This study presents a method using bi-directional reflectance difference function (BRDF) data to invert foliage nitrogen vertical distribution. We developed upper-layer nitrogen inversion index (ULNI), middle-layer nitrogen inversion index (MLNI) and bottom-layer nitrogen inversion index (BLNI) to reflect foliage nitrogen inversion at upper layer, middle layer and bottom layer, respectively. Both ULNI and MLNI were made by the value of the ratio of Modified Chlorophyll Absorption Ration Index to the second Modified Triangular Vegetation Index (MCARI/MTVI2) referred to as canopy nitrogen inversion index (CNII) in this study at ±40° and ±50°, and at ±30° and ±40° view angles, respectively. The BLNI was composed by the value of nitrogen reflectance index (NRI) at ±20° and ±30° view angles. These results suggest that it is feasible to measure foliage nitrogen vertical-layer distribution in a large scale by remote sensing.
In this paper, the fractional variational integrators for fractional variational problems depending on indefinite integrals in terms of the Caputo derivative are developed. The corresponding fractional discrete Euler-...
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Cloud management faces with great challenges, due to the diversity of Cloud resources and ever-changing management requirements. For constructing a management system to satisfy a specific management requirement, a red...
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Cloud management faces with great challenges, due to the diversity of Cloud resources and ever-changing management requirements. For constructing a management system to satisfy a specific management requirement, a redevelopment solution based on existing management system is usually more practicable than developing the system from scratch. However, the difficulty and workload of redevelopment are also very high. As the architecture-based runtime model is causally connected with the corresponding running system automatically, constructing an integrated Cloud management system based on the architecture-based runtime models of Cloud resources can benefit from the model-specific natures, and thus reduce the development workload. Therefore, in this paper, we present an architecture-based approach to managing diverse Cloud resources. First of all, the manageability (such as APIs, configuration files and scripts) of Cloud resources are abstracted as runtime models, which can automatically and immediately propagate any observable runtime changes of the target resources to the corresponding architecture models, and vice versa. Then, a customized model is constructed according to the specific Cloud management requirement. Finally, the operations on the customized model are mapped to the ones on Cloud resource runtime models through model transformation. Thus, all the management tasks can be carried out through executing operations on the customized model. The experiment on a real-world cloud demonstrates the feasibility, effectiveness and benefits of the new approach to integrated management of Cloud resources.
2D-to-3D video conversion is a feasible way to generate 3D programs for the current 3DTV industry. However, for large-scale 3D video production, current systems are no longer adequate in terms of the time and labor re...
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2D-to-3D video conversion is a feasible way to generate 3D programs for the current 3DTV industry. However, for large-scale 3D video production, current systems are no longer adequate in terms of the time and labor required for conversion. In this paper, we introduce a distributed 2D-to-3D video conversion system that includes a 2D-to-3D video conversion module, architecture of the parallel computation on the cloud, and 3D video coding in the system. The system enables cooperation among multiple users in the simultaneous completion of their conversion tasks so that the conversion efficiency is greatly promoted. In the experiments, we evaluate the system based on criteria related to both time consumption and video coding performance.
Communication engineering specialty is an engineering practical and very strong applied specialty. Practice teaching plays an important role of cultivating students' scientific thinking methods, scientific researc...
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ISBN:
(纸本)9781629939742
Communication engineering specialty is an engineering practical and very strong applied specialty. Practice teaching plays an important role of cultivating students' scientific thinking methods, scientific research ability and innovation ability. Through integrated specialty reform, we improve the practice teaching conditions further, optimize the practice teaching content, innovate the teaching mode, strengthen the teaching team and promote the combination of the cultivation of talents, production-practice and social practice, thus improving students' innovation consciousness and practice ability.
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