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Measured Equation of Invariance(MEI) is a new concept in computational electromagnetics. It has been demonstrated that the MEI technique can be used to terminate the meshes very close to the object boundary and still strictly preserves the sparsity of the FD equations. Therefore, the nal system matrix encountered by MEI is a sparse matrix with size similar(More)
Measured Equation of Invariance(MEI) is a new concept in computational electromagnetics. It has been demonstrated that the MEI is such an eecient boundary truncation technique that the meshes can be terminated very close to the object and still strictly preserves the sparsity of the FD equations. Therefore, the nal system matrix encountered by MEI is a(More)
In this paper, we present a new capacitance extraction method named Dimension Reduction Technique (DRT) for 3D VLSI interconnects. The DRT converts a complex 3D problem into a series of cascading simple 2D problems. Each 3D problem is solved separately, so we can choose the most efficient method according to the arrangement of conductors. More importantly,(More)
Measured Equation of Invariance(MEI) is a new concept in computational electromagnetics. It has been demonstrated that the MEI technique can be used to terminate the meshes very close to the object boundary and still strictly preserves the sparsity of the FD equations. Therefore, the nal system matrix encountered by MEI is a sparse matrix with size similar(More)
abstract The key to the method of measured equation of invariance (MEI) is the postulate: \the MEI is invariant to the excitation". In this paper, we proved that the MEI is independent of the excitation with the error bounded by O(h 2), where h is the discretization step. We also proved that the consistent condition jjLL?M=h 2 jj = ", where L is the partial(More)
abstract In this paper, a new method named Dimension Reduction Technique (DRT) is presented for capacitance extraction of 3D multilayer and multiconductor interconnects. In this technique, a complex 3D problem is decomposed to a series of simpler 2D problems. Therefore, it results in dramatical savings in computing time and memory usage. Compared to(More)
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