Accurate estimation of power is a main requirement throughout the use of Complementary Metal–Oxide–Semiconductor Very Large-Scale Integration (CMOS VLSI) because it determines how efficiently energy is used; how hot a device will get from high temperatures; whether a device will work properly over long periods of time...
V. Govindaraj, M. Sheela, P. M. Krishnammal et al.· Discover Computing· 0 citations
This study compares the performance of Back Propagation Neural Network, Support Vector Machine, and Probabilistic Neural Network to classify catastrophic faults in both 16-bit Charge Scaling and Binary Weighted DACs that have experienced process variation such as variable threshold voltage, oxide thickness and temperat...
V. Govindaraj, M. Sheela, M. Muthuraja et al.· Discover Computing· 0 citations
The model achieved remarkable results over various phases, accuracy, precision, recall, and F1-score increased, reaching 97.0%, 96.8%, and 96.9%, respectively, in the final classification phase, demonstrating robust and reliable detection capabilities.
S. Gopalakrishnan, J. Thangamalar, M. Sheela et al.· International Journal of Eng...· 0 citations
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