L3harris Technologies, Inc.

The Boeing Company

Rockwell Collins, Inc.

Seth John Thorup

Kyle R Morrey

Stephen N Jenkins

Brent A Kenney

Michael John McNicholl

George Wu

Calvin Ling

Osama Sami Haddadin

Harold Dee Gardiner

Andrew L Nelson

Stephen M Dudley

Benjamin C Dean

Christopher S Heffernan

Thomas Peter Skowyra

Lee F Carter

Boston C Terry

Alex J Marcum

Armin Hedzic

Raymond Lee Fitzgerald

David A Reed

A radio frequency (RF) system may include at least one RF sensor in an RF environment and at least one RF actuator. The RF system may also include at least one processor that includes a machine learning agent configured to use a machine learning algorithm to generate an RF model to operate the at least one RF actuator based upon the at least one RF sensor. The processor may also include a recommendation training agent configured to generate performance data from the machine learning agent, and change the RF environment based upon the performance data so that the machine learning agent updates the machine learning algorithm.

Recommendation training agent for machine learning algorithm and related methods

One embodiment illustrated herein includes a hardware system for simulating a network physical layer for communication channels. The hardware system includes a plurality of hardware processors configurable to model a network physical layer and communication channels. The hardware processors include an opcode processing unit. The hardware processors further include a programmable state machine coupled to the opcode processing unit. The programmable state machine is configured to be programmed by the opcode processing unit using a low-level hardware programming language comprising opcodes having waveform processing specific semantics so as to configure the state machine for specific waveforms or specific network physical layer characteristics.

Configuring custom hardware to operate in configurable operational modes using a scripting language

A hardware system for simulating a network physical layer for communication channels. The hardware system includes a plurality of hardware processors configurable to model a network physical layer and communication channels. The hardware system is further implemented where the hardware processors are configured such that a single set of hardware, including a single set of gates and registers, is used in a single simulation to model a plurality of virtual routers for different nodes.

Modeling multiple hardware routers in custom hardware

A hardware system for simulating a network physical layer for communication channels. The hardware system includes a plurality of hardware processors configurable to model a physical layer and communication channels. The hardware system includes a first interface coupled to the plurality of hardware processors. The first interface is configured to be coupled to a software simulator comprising a physics model configured to provide model parameters based on modeled communication hardware and a temporal modeling scenario. A second interface is coupled to the plurality of hardware processors. The second interface is configured to be coupled to simulated or real nodes for sending and receiving network data to and from the nodes. The hardware processors are configured to model effects of the physical layer and communication channels on the network data.

Modeling waveform physical layer and channel for simulation using custom hardware

A system for simulating lost data packets. The system includes a first hardware register storing data for fast factors. The fast factors include factors that are time independent with respect to particular data packets. A second hardware register stores slow factors. The slow factors include factors that are time dependent on data packets. Synchronization hardware is coupled to the second hardware register and synchronizes the slow factors with specific data inputs based on dependencies on the data packets. A hardware adder is coupled to the first hardware register and the second hardware register to compute a link budget. The link budget is used in determine probability of loss of data packets. A hardware processor coupled to the hardware adder determines, based on the link budget, if a data packet should be dropped, and when the data packet should be dropped, drops the data packet for simulating a network physical layer.

Synchronizing dynamic link budgets with FPGA based simulation waveform state machines

A hardware system for simulating a network physical layer for communication channels. The hardware system includes a plurality of hardware processors configurable to model a network physical layer and communication channels. The hardware system further includes a multi-point data switch configured to be coupled to various data log points associated with the plurality of hardware processors. The hardware system further includes a RAM coupled to the multi-point data switch, where the RAM is configured to store log data provided by the multi-point data switch as software defined data structures.

High volume data logging from hardware

A computerized method and system of rendering a graphical image containing a volumetric object on an electronic display is provided. The method includes defining, at a processing circuit, the volumetric object as a volume. The volume comprises a plurality of polygons. The method includes rendering the volume for a first plurality of pixels of the electronic display. The volume is described by volume characteristics. The method includes rendering a graphical image for a second plurality of pixels of the electronic display. The graphical image is described by global characteristics. When a view ray for at least one of the second plurality of pixels intersects at least one of the first plurality of pixels, the global characteristics and a proportion of the volume characteristics are combined when rendering the graphical image. The proportion is defined by an extent of the intersection of the view ray.

Volume rendering a graphical 3D scene containing a 3D volumetric object and atmospheric effects

A method for verifying the connectivity of software applications hosted on networked computers. The connectivity of hosted function applications to be loaded into networked computers is verified and validated using quasi-hosted function applications that simulate the communications functions (i.e., connectivity) of those hosted function applications. The quasi-hosted function applications are run on the same hardware that the real hosted function applications will be run on. Furthermore, the connectivity of a real hosted function application loaded into one computer can be verified and validated by simulating communications of that real hosted function application with a multiplicity of quasi-hosted function applications running on the networked computers.

Growing community of inventors

Sandy, UT, United States of America

Seth John Thorup