公开(公告)号：US20220383043A1

公开(公告)日：2022-12-01

申请号：US17334392

申请日：2021-05-28

Applicant: Oracle International Corporation

Inventor： Matthew T. Gerdes ,  Guang C. Wang ,  Kenny C. Gross ,  Timothy David Cline

IPC: G06K9/62 ,  G06K9/00

Abstract: The disclosed system produces synthetic signals for testing machine-learning systems. During operation, the system generates a set of N composite sinusoidal signals, wherein each of the N composite sinusoidal signals is a combination of multiple constituent sinusoidal signals with different periodicities. Next, the system adds time-varying random noise values to each of the N composite sinusoidal signals, wherein a standard deviation of the time-varying random noise values varies over successive time periods. The system also multiplies each of the N composite sinusoidal signals by time-varying amplitude values, wherein the time-varying amplitude values vary over successive time periods. Finally, the system adds time-varying mean values to each of the N composite sinusoidal signals, wherein the time-varying mean values vary over successive time periods. The time-varying random noise values, amplitude values and mean values can be selected through a roll-of-the-die process from a library of values, which are learned from industry-specific signals.

公开(公告)号：US12189715B2

公开(公告)日：2025-01-07

申请号：US17334392

申请日：2021-05-28

Applicant: Oracle International Corporation

Inventor： Matthew T. Gerdes ,  Guang C. Wang ,  Kenny C. Gross ,  Timothy David Cline

IPC: G06F18/214 ,  G06F1/02 ,  G06N3/08

Abstract: The disclosed system produces synthetic signals for testing machine-learning systems. During operation, the system generates a set of N composite sinusoidal signals, wherein each of the N composite sinusoidal signals is a combination of multiple constituent sinusoidal signals with different periodicities. Next, the system adds time-varying random noise values to each of the N composite sinusoidal signals, wherein a standard deviation of the time-varying random noise values varies over successive time periods. The system also multiplies each of the N composite sinusoidal signals by time-varying amplitude values, wherein the time-varying amplitude values vary over successive time periods. Finally, the system adds time-varying mean values to each of the N composite sinusoidal signals, wherein the time-varying mean values vary over successive time periods. The time-varying random noise values, amplitude values and mean values can be selected through a roll-of-the-die process from a library of values, which are learned from industry-specific signals.