Discrete cosine transform: algorithms, advantages, applications
Discrete cosine transform: algorithms, advantages, applications
Fast methods for extraction and sparsification of substrate coupling
Proceedings of the 37th Annual Design Automation Conference
HSpeedEx: a high-speed extractor for substrate noise analysis in complex mixed signal SOC
Proceedings of the 39th annual Design Automation Conference
Parasitics extraction involving 3-D conductors based on multi-layered Green's function
ASP-DAC '06 Proceedings of the 2006 Asia and South Pacific Design Automation Conference
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A semi-analytical technique for computation of the frequency- behavior of silicon substrates is demonstrated. The technique uses a boundary element approach, that utilizes the complex substrate Green Function and the two-dimensional Fast Fourier Transform. The resultant dense system matrix is sparsified by application of orthogonal transform operators on the matrix representing the system. Three transform operators are evaluated for this purpose - the Discrete Cosine Transform (DCT), the Discrete Wavelet Transform (DWT) and the Discrete Hadamard Transform (DHT). The application of any one of these operators provides a rigorous sparsification technique, which significantly reduces the computation time. The Green Function is computed in the two layers at the top of the substrate. This is done so that contacts in the oxide layer can be included in the substrate model, along with contacts in the silicon substrate. Hence, substrate loss terms in metal interconnect lines and in line-to- line interaction models, can be evaluated using this technique. Extraction of a simple circuit-simulator compatible model from frequency-domain data is discussed.