Training method and test apparatus using the same
AssigneeSamsung Electronics Co., Ltd.
InventorsKwang Kyu Kim, Jae-Il Choi
Life of this patent
Estimating the term…
Abstract
Provided is a training method capable of reducing or minimizing a training time. The training method includes, for each of devices to be tested, calculating a first eye width at which a first signal and a second signal synchronize with each other at a first operation speed, and calculating a second eye width at which the first signal and the second signal synchronize with each other at a second operation speed different from the first operation speed; performing machine learning on the first eye width and the second eye width to derive a model showing a relation between operation speeds and eye widths; and calculating a third eye width corresponding to a third operation speed different from the first operation speed and the second operation speed, using the model.
Claims20
A training method comprising:
- for each of first devices to be tested, calculating a first eye width at which a first signal and a second signal synchronize with each other at a first operation speed, and calculating a second eye width at which the first signal and the second signal synchronize with each other at a second operation speed different from the first operation speed;
- deriving a model showing a relation between operation speeds and eye widths by performing machine learning on the first eye width and the second eye width;
- and
- using the model to calculate a third eye width corresponding to a third operation speed different from the first operation speed and the second operation speed.
A training method comprising:
- for each of first devices to be tested, calculating a first eye width at which a first signal and a second signal synchronize with each other at a first operation speed, and calculating a second eye width at which the first signal and the second signal synchronize with each other at a second operation speed different from the first operation speed;
- performing machine learning on the first eye width and the second eye width to derive a linear regression model showing a relation between operation speeds and eye widths by using a gradient descent method to calculate parameters of the linear regression model;
- calculating a third eye width corresponding to a third operation speed, using the linear regression model;
- finding a third fail-to-pass point, while adjusting a delay of the first signal at the third operation speed;
- and
- determining from the third fail-to-pass point to a point obtained by adding the third eye width to the third fail-to-pass point, as a position of a valid window margin.
A test apparatus comprising:
- output nodes configured to electrically connect to first devices to be tested;
- a timing generator configured to provide a first signal and a second signal to the first devices to be tested through the output nodes;
- and
- a controller configured to control the timing generator,
- wherein the controller is configured to calculate a first eye width at which the first signal and the second signal synchronize with each other at a first operation speed, and calculate a second eye width at which the first signal and the second signal synchronize with each other at a second operation speed different from the first operation speed, for each of first devices to be tested,
- wherein the controller is configured to perform machine learning on the first eye width and the second eye width to derive a model showing a relation between operation speeds and eye widths, and
- wherein the controller is configured to calculate a third eye width corresponding to a third operation speed different from the first operation speed and the second operation speed by using the model.
Dependencies are inferred from the claim text.