Eagle Technology, LLC

Chad Chung Lau

Mark Donald Rahmes

David Bruce Chester

Thomas Jay Billhartz

Jason Calvert

Vladislav M Fomitchev

Glenn Boudreaux

Clarke O Fowler

Don S George

Andrea Ballester

Daniel Garcia

A cognitive radio system may include cognitive radio frequency (RF) radios and a controller configured to selectively change at least one operating parameter of the cognitive RF radios based upon a cognitive group hierarchy. The cognitive group hierarchy may include a first group based upon a signal modulation classification, a second group based upon a waveform requirement, a third group based upon an optimal cognitive RF radio path, a fourth group based upon a cognitive RF radio dynamic spectrum allocation, and a fifth group based upon frequency hopping.

Cognitive radio system providing operating parameter changes based upon cognitive group hierarchy and related methods

Systems and methods for operating a communication device. The methods comprise: receiving a signal at the communication device; performing, by the communication device, one or more machine learning algorithms using at least one feature of the signal as an input to generate a plurality of scores (each score representing a likelihood that the signal was modulated using a given modulation type of a plurality of different modulation types); assigning a modulation class to the signal based on the plurality of scores; determining whether a given wireless channel is available based at least on the modulation class assigned to the signal; and selectively using the given wireless channel for communicating signals based on results of the determining.

Systems and methods for controlling communications based on machine learned information

A cognitive radio device may include a radio frequency (RF) detector, an RF transmitter having a selectable hopping frequency window, and a controller. The controller may be configured to cooperate with the RF detector and RF transmitter to detect a jammer signal, determine a jammer type associated with the jammer signal from among a plurality of different jammer types based upon a game theoretic model, and operate the RF transmitter to change the selectable hopping frequency window responsive to the determined jammer type of the jammer signal.

Cognitive radio providing jammer type detection based upon game theoretic model and related methods

Systems and methods for providing a fin structure. The fin structure may be employed in a heat exchanger. The fin structure comprises: a support structure; and a plurality of fins disposed on the support structure via additive manufacturing so as to facilitate a change in direction of a fluid flowing through the fin structure. The fins comprise first fins that have centers arranged in accordance with a phyllotaxis or Fibonacci pattern.

Heat exchanger

Systems and methods for operating a receiver. The methods comprise: receiving, at the receiver, a combined waveform comprising a combination of a desired signal and an interference signal; and performing, by the receiver, demodulation operations to extract the desired signal from the combined waveform. The demodulation operations comprise: obtaining, by the receiver, machine learned models for recovering the desired signal from combined waveforms; comparing, by the receiver, at least one characteristic of the received combined waveform to at least one of the machine learned models; and determining a value for at least one symbol of the desired signal based on results of the comparing.

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Melbourne, FL, United States of America

Chad Chung Lau