In this work, a parallel adaptive algorithm for the computation of a multidimensional integral on heterogeneous GPU and multicore based systems is described. Two different strategies have been combined together in the...
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ISBN:
(纸本)9783642552243
In this work, a parallel adaptive algorithm for the computation of a multidimensional integral on heterogeneous GPU and multicore based systems is described. Two different strategies have been combined together in the algorithm: a first procedure is responsible for the load balancing among the threads on the multicore CPU and a second one is responsible for an efficient execution on the GPU of the computational kernel. The performance is analyzed and experimental results on a system with a quad-core CPUs and two GPUs have been achieved.
Traditional real-time active noise control (ANC) has been widely used to reduce environmental noise, usually using the filtered-x least mean square (FxLMS) algorithm to adjust the control filter coefficients. However,...
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In this paper, we consider the problem of identifying unknown parameters of non-stationary systems. Let us assume that the non-stationary parameter of the system can be represented by the outputs of linear generators ...
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In this paper, a sliding mode control algorithm based on variable mass estimation for quadrotor is studied. Firstly, based on the Newton Euler's formula, a mathematical model of the variable-mass quadrotor is esta...
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ANC systems have emerged as the most widely adopted technologies in voice communications. This paper purpose a comparison between the adaptive approaches in time and frequency domain, which is used to model, design an...
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This paper proposes some efficient and accurate adaptive two-grid (ATG) finite element algorithms for linear and nonlinear PDEs. The main idea of these algorithms is to utilize the solutions on the kth-level adaptive ...
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This paper proposes some efficient and accurate adaptive two-grid (ATG) finite element algorithms for linear and nonlinear PDEs. The main idea of these algorithms is to utilize the solutions on the kth-level adaptive meshes to find the solutions on the (k+1)th-level adaptive meshes which are constructed by performing adaptive element bisections on the kth-level adaptive meshes. These algorithms transform nonsymmetric positive definite (non-SPD) PDEs (resp., nonlinear PDEs) into symmetric positive definite (SPD) PDEs (resp., linear PDEs). The proposed algorithms are both accurate and efficient due to the following advantages: They do not need to solve the nonsymmetric or nonlinear systems;the degrees of freedom are very small, they are easily implemented, and the interpolation errors are very small. Next, this paper constructs residual-type a posteriori error estimators which are shown to be reliable and efficient. The key ingredient in proving the efficiency is to establish an upper bound of the oscillation terms, which may not be higher-order terms due to the low regularity of the numerical solution. Furthermore, the convergence of the algorithms is proved when bisection is used for the mesh refinements. Finally, numerical experiments are provided to verify the accuracy and efficiency of the ATG finite element algorithms compared to regular adaptive finite element algorithms and two-grid finite element algorithms [J. Xu, SIAM J. Numer. Anal., 33 (1996), pp. 1759-1777].
Label efficiency has become an increasingly important objective in deep learning applications. Active learning aims to reduce the number of labeled examples needed to train deep networks, but the empirical performance...
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Monitoring physiological and biomechanical variables plays an important role in assessing human health in several scenarios, including sports. In this context, there is an increasing demand for wearable devices that c...
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Probabilistic maximum coverage (PMC) is an important problem that can model many network applications, including mobile crowdsensing, network content delivery, and dynamic channel allocation, where an operator chooses...
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The article proposes a fast, two-stage method for the identification of nonstationary systems. The method uses iterative reweighting to robustify the identification process against the outliers in the measurement nois...
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