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We develop a new time-domain method that is naturally matrix free, i.e., requiring no matrix solution, regardless of whether the discretization is a structured grid or an unstructured mesh. Its matrix-free property, manifested by a naturally diagonal mass matrix, is independent of the element shape used for discretization and its implementation is straightforward. No dual mesh, interpolation, projection,...
In this paper, we present a new time-domain method that is naturally matrix free, i.e., requiring no matrix solution, regardless of whether the discretization is a structured grid or an unstructured mesh. Its matrix-free property is independent of the element shape used for discretization, and its implementation is straightforward. No interpolations, projections, and mass lumping are required. The...
We develop an accurate 3-D matrix-free time-domain method independent of the element shape used for discretization. The accuracy and stability of the proposed method are shown to be theoretically guaranteed. No dual mesh is needed. The tangential continuity of the fields is satisfied across the element interface. Numerical experiments on unstructured 3-D meshes with arbitrarily shaped tetrahedron...
In this paper, we develop a new time-domain method that is naturally matrix free and independent of element shape used for discretization. No extra modification on traditional vector bases is required. Its implementation is straightforward. The accuracy and stability of the proposed method are shown to be guaranteed. Numerical experiments on a variety of unstructured tetrahedral meshes have validated...
Given an accuracy requirement, there exists a minimal-order model to represent the field solution in a general electromagnetic problem involving lossless and/or lossy inhomogeneous materials with arbitrarily shaped structures. In this paper, we develop a fast time-domain algorithm to find such a minimal-order model efficiently. Numerical simulations of integrated circuits and package problems have...
Distinguish accurately known and unknown attack is a key element to classification model in order to increase detection accuracy of unknown attacks. This paper proposes ArtiAnomalyG algorithm which expands sparse region and injects anomaly instances given the class label anomaly into the training data. Filtering experiment result shows that possibility of causing the collision with original instances...
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