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• W2967872297 abstract "We present recent developments on post-production calibration of analog and radio frequency (RF) integrated circuits (ICs) mainly focusing on on-chip solutions. Specifically, we summarize the state-of-the-art on both direct and statistical calibration techniques. The latter typically employ on-die sensors, which estimate the circuit under test (CUT) performances and tuning knobs, which along with machine learning-based methods are capable of calibrating the CUT. Existing sensors, tuning knobs and machine learning-based implementations are discussed and their limitations are outlined. Lastly, a fully integrated new architecture for on-chip calibration of a low-noise amplifier (LNA) through the use of an analog neural network is introduced." @default.
• W2967872297 created "2019-08-22" @default.
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• W2967872297 date "2019-07-01" @default.
• W2967872297 modified "2023-09-27" @default.
• W2967872297 title "Post-Production Calibration of Analog/RF ICs: Recent Developments and A Fully Integrated Solution" @default.
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• W2967872297 doi "https://doi.org/10.1109/smacd.2019.8795278" @default.
• W2967872297 hasPublicationYear "2019" @default.
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