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This paper considers the application of finite-time control to a Cucker-Smale flocking model of autonomous agents with collision avoidance. A mathematical expression for the upper bound on the flocking time is derived. Previous results without considering collision avoidance showed that the flocking time decreases as the number of robots in the flock increases, which is counter-intuitive. We showed...
We consider the problem of modeling data matrices with locally low rank (LLR) structure, a generalization of the popular low rank structure widely used in a variety of real world application domains ranging from medical imaging to recommendation systems. While LLR modeling has been found to be promising in real world application domains, limited progress has been made on the design of scalable algorithms...
Laser rangefinders are very popular sensors in robot localization due to their accuracy. Typically, localization algorithms based on these sensors compare range measurements with previously obtained maps of the environment. As many indoor environments are highly symmetrical (e.g., most rooms have the same layout and most corridors are very similar) these systems may fail to recognize one location...
Joint sparse representation (JSR) models have been widely applied into the field of hyperspectral image (HSI) classification. However, most of JSR-based models adopt the Frobenius norm to measure the reconstruction error, which ignores the structural information of the small patch. In this paper, we propose a nuclear-norm joint sparse representation (NuJSR) model for hyperspectral image classification...
This paper deals with the design of a Proportional Multiple Integral (PMI) observer for Takagi-Sugeno systems with immeasurable premise variables subjected to unknown inputs. The introduction of an output error injection in the premise variable of the PMI observer allows to significantly reduce the conservatism of LMI-based stability conditions. A simulation example of a chaotic system is given to...
We consider a large system populated by n anonymous nodes that communicate through asynchronous and pair-wise interactions. The aim of these interactions is for each node to converge toward a global property of the system, that depends on the initial state of each node. In this paper we focus on both the counting and proportion problems. We show that for any δ ∊ (0, 1), the number of interactions...
Deep embeddings answer one simple question: How similar are two images? Learning these embeddings is the bedrock of verification, zero-shot learning, and visual search. The most prominent approaches optimize a deep convolutional network with a suitable loss function, such as contrastive loss or triplet loss. While a rich line of work focuses solely on the loss functions, we show in this paper that...
The traditional iterative closest point (ICP) algorithm could register two points sets well, but it is easily affected by local dissimilar. To deal with this problem, this paper proposes an isotropic scaling ICP algorithm with corner point constraint. First, an objective function is proposed under the guidance of the corner points, as the corner points can preserve the similar of the whole shapes...
Predicting the desirability and number of student applications to universities is a challenging and dynamic undertaking. Student applications are affected by a variety of factors ranging from those related to the university itself and its surrounding community, to factors up to the national level, including perceptions of international relations. This paper proposes a way of modeling this complex...
This paper develops a model to show the effects of soft errors on power flow calculations. We create artificial bit-flips and apply them to solve linear equations obtained in Fast Decoupled Load Flow (FDLF) method. With this, we aim to represent the sensitivity of FDLF iteration against soft errors with a statistical view by using different numerical fault injection scenarios. The study focuses on...
The pre-exascale systems are expected to have a significant amount of hierarchical and heterogeneous on-node memory, and this trend of system architecture in extreme-scale systems is expected to continue into the exascale era. Along with hierarchical-heterogeneous memory, the system typically has a high-performing network and a compute accelerator. This system architecture is not only effective for...
Species distribution modeling (SDM) calculates a species’ probabilistic distribution by combining Environmental raster layers with species datasets. Such models can help to answer complex questions in Ecology/Biology/Health, e.g., by calculating impacts of climate changes in Biodiversity, or the potential for a disease spread (vectors’ modeling). Machine learning is largely applied in SDM, being the...
This paper compares the stochastic convergence of the Uniform Random number generators of two simulation software namely Matlab and Python and establishes the significance in choosing the right random number generator for error propagation studies. It further discusses about the application of Gaussian type of these random number generators to nonlinear cases of Error propagation using the Monte Carlo...
In our country, type and quantity of network attacks have continued to grow, China's network infrastructure and the important information system is also facing serious security challenges. A variety of network attacks and other network security incidents have become the bottleneck in the development of our national economy, and even endanger the social stability and national security of the important...
Digital predistortion (DPD) is an effective power amplifier (PA) linearization technique improving the system energy efficiency. At this point, real-time DPD adaptation is still an open issue due to the high computational complexity during the coefficients estimation procedure. Online censoring approach, which is effective in reducing the redundant data samples, can be applied in the DPD coefficients...
We revisit the Wilson-Dirac operator, also referred as Dslash, on NUMA manycore vector machines and thereby seek an efficient supercomputing implementation. Quantum Chro- moDynamics (QCD) is the theory of the strong nuclear force and its discrete formalism is the so-called Lattice Quantum ChromoDynamics (LQCD). Wilson-Dirac is the major computing kernel in LQCD, where a special attention is paid to...
Radial Basis Function(RBF) mesh deformation method has been widely used in CFD simulations with moving boundaries due to its high robustness and accuracy. The original implementation of the RBF mesh deformation method in OpenFOAM(a widely used CFD software) is purely serial with relatively low computational performance. To reduce the time cost of the mesh motion in large-scale simulations, this paper...
A special class of recurrent neural network, termed Zhang neural network (ZNN), has been recently proposed for solving various dynamic problems, and has shown excellent performance in the real-valued domain. In this paper, a new complex-valued ZNN model (termed CVZNN model) is firstly proposed and investigated for online solution of dynamic complex-valued matrix pseudoinverse. Particularly, a novel...
This paper proposed a novel fractional-order Vicsek model (FOVM), which can effectively improve the convergence performance of the original Vicsek model. Numeral experiment results show that there is the optimal value of the fractional order of the FOVM with which the self-propelled particles can achieve the best convergence performance.
Graph matching is a fundamental problem in computer vision and pattern recognition area. In general, it can be formulated as an Integer Quadratic Programming (IQP) problem. Since it is NP-hard, approximate relaxations are required. In this paper, a new graph matching method has been proposed. There are three main contributions of the proposed method: (1) we propose a new graph matching relaxation...
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