University of Utah Research Foundation

Battelle Energy Alliance, LLC

Aniqua Z Baset

Sneha Kumar Kasera

Kurt Warren Derr

Christopher D Becker

Samuel Ramirez

Disclosed embodiments relate to ensemble wireless signal classification and systems and devices the incorporate the same. Some embodiments of ensemble wireless signal classification may include energy-based classification processes and machine learning-based classification processes. In some embodiments, incremental machine learning techniques may be incorporated to add new machine learning-based classifiers to a system or update existing machine learning-based classifiers.

Spectrum monitoring and analysis, and related methods, systems, and devices

Processing flows and related systems and methods are disclosed. A computing system includes one or more data interfaces, one or more other components, and a controller. The one or more data interfaces are configured to provide an interface to a data source. The one or more other components include one or more controller plugins, one or more processing nodes, or both the one or more controller plugins and the one or more processing nodes. The controller is configured to manage interactions between the one or more data interfaces and the one or more other components and enable a user to chain together the one or more data interfaces and the one or more other components according to one or more flows. The one or more controller plugins are configured to provide results of the one or more flows to one of a user interface and a system interface.

Processing flows and related systems and methods are disclosed

Wireless signal classifiers and systems that incorporate the same may include an energy-based detector configured to analyze an entire set of measurements and generate a first signal classification result, a cyclostationary-based detector configured to analyze less than the entire set of measurements and generate a second signal classification result; and a classification merger configured to merge the first signal classification result and the second signal classification result. Ensemble wireless signal classification and systems and devices the incorporate the same are disclosed. Some ensemble wireless signal classification may include energy-based classification processes and machine learning-based classification processes. In some embodiments, incremental machine learning techniques may be incorporated to add new machine learning-based classifiers to a system or update existing machine learning-based classifiers.

Growing community of inventors

Salt Lake City, UT, United States of America

Aniqua Z Baset