Unified pre-processing steps reducing the PCB design space to enable ML applications for signal and power integrity analysis

Machine Learning (ML) applications need large quantities of data spanning the complete Printed Circuit Board (PCB) design space. This design space needs to be reduced to the subset of relevant PCB configurations, i.e. those yielding network parameters which are different from each other. For this purpose a preliminary design space analysis is carried out and pre-processing steps are presented to unify the application of ML in the Signal and Power Integrity domains and pave the way to a standardized PCB representation format.

Subjects

Database | Machine Learning | Power Integrity | Printed Circuit Board | Signal Integrity

DDC Class

621.3: Electrical Engineering, Electronic Engineering

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Unified pre-processing steps reducing the PCB design space to enable ML applications for signal and power integrity analysis