Rohde & Schwarz had one patents in digitalization during Q2 2024. The patent filed by Rohde & Schwarz GmbH & Co KG in Q2 2024 describes a method for assessing log-files by accessing a data storage containing multiple log-files, identifying a group of log-files closest to the log-file being assessed, and returning this group for further analysis. Additionally, the patent covers methods for grouping log-files and a system for processing log-files. GlobalData’s report on Rohde & Schwarz gives a 360-degree view of the company including its patenting strategy. Buy the report here.
Rohde & Schwarz had no grants in digitalization as a theme in Q2 2024.
Recent Patents
Application: Method of assessing a log-file, method of grouping several log-files, and system for processing at least one log-file (Patent ID: US20240168920A1)
The patent filed by Rohde & Schwarz GmbH & Co KG describes a method for assessing log-files by accessing a data storage containing multiple log-files, identifying a group of log-files closest to the log-file to be assessed, and returning this group for further analysis. The method involves grouping log-files based on underlying patterns, generating compressed representations for efficient processing, and automatically labeling non-labeled log-files based on labeled ones. The system for processing log-files includes a processing circuit, potentially within a test and measurement device, connected to a front-end for presenting information on the identified log-file group.
The method and system outlined in the patent aim to streamline the analysis of log-files by efficiently grouping them based on patterns and compressed representations. By automatically labeling log-files and providing a user-friendly interface for further analysis, the system enhances the assessment process. The use of different measurement setups and remote data storage modules further adds flexibility and scalability to the log-file processing system. Overall, the patent introduces a comprehensive approach to log-file assessment that combines pattern recognition, compression techniques, and automated labeling to improve efficiency and accuracy in analyzing log-files.
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