The Aerospace Corporation

Esteban Luis Valles

Philip A Dafesh

Donna Branchevsky

Kyle A Logue

Sebastian Olsen

Raghavendra S Prabhu

Andres Vila Casado

Fusion of trained artificial intelligence (AI) neural networks to produce more accurate classifications is disclosed. Concatenation from each network being merged may be performed. The new set of features, which includes the concatenated layers, is then fed through a new classifier to form a single final classifier that uses the best parts of each input classifier.

Fusing output of artificial intelligence networks

Cognitive anti-jam receiver systems and associated methods are provided. The systems and methods may include a signal analysis module that processes a baseband signal to determine one or more signal characteristics of the baseband signal, the baseband signal comprising at least a desired signal; a cognitive decision unit that receives the one or more signal characteristics from the signal analysis module, and generates at least one first adaptive parameter; and at least one anti-jam processing module that processes the baseband signal to generate a modified signal that reduces an impact of at least one jammer signal on a quality of reception of the desired signal from the baseband signal, where processing by the at least one anti-jam processing module may be based at least in part on the received at least one first adaptive parameter from the cognitive decision unit.

Cognitive anti-jam receiver systems and associated methods

Growing community of inventors

Los Angeles, CA, United States of America

Esteban Luis Valles