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  • Open Access

    ARTICLE

    Power Prediction of VLSI Circuits Using Machine Learning

    E. Poovannan*, S. Karthik

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 2161-2177, 2023, DOI:10.32604/cmc.2023.032512

    Abstract The difference between circuit design stage and time requirements has broadened with the increasing complexity of the circuit. A big database is needed to undertake important analytical work like statistical method, heat research, and IR-drop research that results in extended running times. This unit focuses on the assessment of test strength. Because of the enormous number of successful designs for current models and the unnecessary time required for every test, maximum energy ratings with all tests cannot be achieved. Nevertheless, test safety is important for producing trustworthy findings to avoid loss of output and harm to the chip. Generally, effective… More >

  • Open Access

    ARTICLE

    Model Reduction by Generalized Falk Method for Efficient Field-Circuit Simulations

    Loc Vu-Quoc1,*, Yuhu Zhai2 and Khai D. T. Ngo3

    CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.3, pp. 1441-1486, 2021, DOI:10.32604/cmes.2021.016784

    Abstract The Generalized Falk Method (GFM) for coordinate transformation, together with two model-reduction strategies based on this method, are presented for efficient coupled field-circuit simulations. Each model-reduction strategy is based on a decision to retain specific linearly-independent vectors, called trial vectors, to construct a vector basis for coordinate transformation. The reduced-order models are guaranteed to be stable and passive since the GFM is a congruence transformation of originally symmetric positive definite systems. We also show that, unlike the Pad´e-via-Lanczos (PVL) method, the GFM does not generate unstable positive poles while reducing the order of circuit problems. Further, the proposed GFM is… More >

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