Simulated circuit data supporting the research of analog filter circuits
What's in it
The dataset contains simulation-generated data for automated fault diagnosis in analog and mixed-signal (AMS) electronic circuits. The dataset was developed to support machine learning-based fault classification and identification in complex electronic systems exhibiting non-linear behavior and sensitivity to parameter variations.The dataset includes data collected from six different analog and mixed-signal circuit configurations operating under both fault-free and faulty conditions. The considered circuits include active filter structures such as Sallen-Key filters, Chebyshev filters and other representative AMS circuit topologies. Each circuit is simulated for multiple fault scenarios including component parametric deviations, open-circuit faults and short-circuit faults.
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