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Titlebook: Speeding-Up Radio-Frequency Integrated Circuit Sizing with Neural Networks; João L. C. P. Domingues,Pedro J. C. D. C. Vaz,Rica Book 2023 T

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楼主: Radiofrequency
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https://doi.org/10.1007/978-3-031-25099-6machine learning; deep learning; neural networks; computational intelligence; analog circuits
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João L. C. P. Domingues,Pedro J. C. D. C. Vaz,RicaDescribes the developments in the field of machine/deep learning and electronic design automation.Presents the process, Voltage and Temperature Corner Performance Estimator using ANNs.Applies deep lea
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978-3-031-25098-9The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
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Speeding-Up Radio-Frequency Integrated Circuit Sizing with Neural Networks978-3-031-25099-6Series ISSN 2191-530X Series E-ISSN 2191-5318
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Introduction,C) design creates a large design productivity gap. The level of automation provided by electronic design automation (EDA) tools for analog IC design is not even close to the level of automation found in digital design. Moreover, as analog IC design follows very heterogeneously and knowledge-intensiv
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Convergence Classifier and Frequency Guess Predictor Based on ANNs,led oscillators (VCOs), which play a crucial role in ultralow-power radios, different tradeoffs between power, phase noise, range, frequency pushing, and silicon area, turn their design into a cumbersome task without the assistance of electronic design automation (EDA), a field where simulation-base
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