Abstract: A system may include circuitry configured to couple a first end of a first resistor to a first input terminal of a line driver and couple a first end of a second resistor to a second input terminal of the line driver. The circuitry may be configured to receive, at a second end of the first resistor, a first signal. The circuitry may be configured to receive, at a second end of the second resistor, a second signal. The circuitry may be configured to set at least one of the first resistor or the second resistor to cause the line driver to output a predetermined range of output voltages, based at least on a voltage sensed from at least one of the first signal or the second signal.

Abstract: A system may include circuitry configured to couple a first end of a first resistor to a first input terminal of a line driver, and couple a first end of a second resistor to a second input terminal of the line driver. The circuitry may be configured to receive, at a second end of the first resistor, a first signal. The circuitry may be configured to receive, at a second end of the second resistor, a second signal. The circuitry may be configured to set resistance of at least one of the first resistor or the second resistor such that the line driver outputs a predetermined range of output voltages based at least on a voltage sensed from at least one of the first signal or the second signal.

Abstract: There is provided a method of predicting performance in electronic design based on machine learning using at least one processor, the method including: providing a first machine learning model configured to predict performance data for an electronic system based on a set of input design parameters for the electronic system; providing a second machine learning model configured to generate a new set of parameter values for the set of input design parameters for the electronic system based on a desired performance data provided for the electronic system; generating, using the second machine learning model, the new set of parameter values for the set of input design parameters for the electronic system based on the desired performance data provided for the electronic system; evaluating the set of input design parameters having the new set of parameter values for the electronic system to obtain an evaluated performance data associated with the set of input design parameters having the new set of parameter values;

Abstract: There is provided a method of predicting performance in electronic design based on machine learning using at least one processor, the method including: providing a first machine learning model configured to predict performance data for an electronic system based on a set of input design parameters for the electronic system; providing a second machine learning model configured to generate a new set of parameter values for the set of input design parameters for the electronic system based on a desired performance data provided for the electronic system; generating, using the second machine learning model, the new set of parameter values for the set of input design parameters for the electronic system based on the desired performance data provided for the electronic system; evaluating the set of input design parameters having the new set of parameter values for the electronic system to obtain an evaluated performance data associated with the set of input design parameters having the new set of parameter values;