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- W2079556487 abstract "This paper applies an improved method for testing the signal-to-noise ratio (SNR) of Analogue-to-Digital Converters (ADC). In previous work, a noisy and nonlinear pulse signal is exploited as the input stimulus to obtain the signature results of ADC. By applying a machine-learning-based approach, the dynamic parameters can be predicted by using the signature results. However, it can only estimate the SNR accurately within a certain range. In order to overcome this limitation, an improved method based on work [1] is applied in this work. It is validated on the Labview model of a 12-bit 80 Ms/s pipelined ADC with a pulse- wave input signal of 3 LSB noise and 7-bit nonlinear rising and falling edges." @default.
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- W2079556487 date "2010-06-01" @default.
- W2079556487 modified "2023-09-26" @default.
- W2079556487 title "Improved method for SNR prediction in machine-learning-based test" @default.
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- W2079556487 doi "https://doi.org/10.1109/ims3tw.2010.5503007" @default.
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