18158181. TRAINING METHOD AND TEST APPARATUS USING THE SAME simplified abstract (SAMSUNG ELECTRONICS CO., LTD.)
Contents
TRAINING METHOD AND TEST APPARATUS USING THE SAME
Organization Name
Inventor(s)
Kwang Kyu Kim of Suwon-si (KR)
TRAINING METHOD AND TEST APPARATUS USING THE SAME - A simplified explanation of the abstract
This abstract first appeared for US patent application 18158181 titled 'TRAINING METHOD AND TEST APPARATUS USING THE SAME
Simplified Explanation
The patent application describes a training method that reduces the time required for training. Here are the key points:
- The method involves calculating the synchronization of signals at different operation speeds for each device to be tested.
- The first eye width is calculated at a specific operation speed, and the second eye width is calculated at a different operation speed.
- Machine learning is performed on the calculated eye widths to create a model that shows the relationship between operation speeds and eye widths.
- Using this model, the third eye width corresponding to a different operation speed can be calculated.
Potential applications of this technology:
- This training method can be applied in various industries where devices need to be tested and trained, such as electronics, telecommunications, and manufacturing.
- It can be used in the development and testing of new devices to optimize their performance and reduce training time.
Problems solved by this technology:
- The training method reduces the time required for training devices, which can be a time-consuming process.
- It provides a more efficient way to calculate and optimize the synchronization of signals at different operation speeds.
Benefits of this technology:
- The method saves time and resources by reducing the training time for devices.
- It improves the overall performance and efficiency of devices by optimizing the synchronization of signals at different operation speeds.
- The use of machine learning allows for a more accurate and precise calculation of eye widths and their relationship with operation speeds.
Original Abstract Submitted
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.
