Abstract: Methods and systems including computer programs encoded on computer storage media, for training and deploying machine-learned communication over RF channels.

Abstract: Methods and systems including computer programs encoded on computer storage media, for training and deploying machine-learned communication over RF channels.

Abstract: A method includes obtaining samples of radio-frequency (RF) uplink data signals received wirelessly at a radio unit of a radio access network, the RF uplink data signals including a first RF uplink data signal received from a user device; providing the samples of the RF uplink data signals as input to at least one machine learning model; in response to providing the samples of the RF uplink data signals as input to the at least one machine learning model, obtaining based on an output of the at least one machine learning model, recovered data of the RF uplink data signals; and sending the recovered data of the RF uplink signals to a destination device.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for correcting distortion of radio signals A transmit radio signal corresponding to an output of a transmitting radio signal processing system is obtained. A pre-distorted radio signal is then generated by processing the transmit radio signal using a nonlinear pre-distortion machine learning model. The nonlinear pre-distortion machine learning model includes model parameters and at least one nonlinear function to correct radio signal distortion or interference. A transmit output radio signal is obtained by processing the pre-distorted radio signal through the transmitting radio signal processing system. The transmit output radio signal is then transmitted to one or more radio receivers.

Abstract: A method includes obtaining, using a specified protocol of a radio access network, low-level signal data corresponding to a radio frequency (RF) signal processed in the radio access network; providing the low-level signal data as input to at least one machine learning network; in response to providing the low-level signal data as input to the at least one machine learning network, obtaining, as an output of the at least one machine learning network, metadata providing information on one or more characteristics of the RF signal; and controlling an operation of the radio access network based on the metadata.

Abstract: Aspects of the present disclosure provide a betatron for accelerating electrons. For example, the betatron can include magnet core parts spaced apart by an air gap. At least one main coil can be arranged on the magnet core parts. A betatron tube can be arranged in the air gap for electrons to circulate therein. A control circuit can be electrically coupled to the main coil. The control circuit can be configured to control a main coil current flowing through the main coil, such that as the control circuit increases the main coil current during a current ramp up period, the control circuit maintains the main coil current at a constant level during an injection period when the electrons are injected into the betatron. The current ramp up period can include a short pause and the injection period.

Abstract: Methods and systems including computer programs encoded on computer storage media, for training and deploying machine-learned communication over RF channels.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer-storage media, for detecting and classifying radio signals. The method includes obtaining one or more radio frequency (RF) snapshots corresponding to a first set of signals from a first RF source; generating a first training data set based on the one or more RF snapshots; annotating the first training data set to generate an annotated first training data set; generating a trained detection and classification model based on the annotated first training data set; and providing the trained detection and classification model to a sensor engine to detect and classify one or more new signals using the trained detection and classification model.

Abstract: Methods and systems including computer programs encoded on computer storage media, for training and deploying machine-learned communication over RF channels.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for correcting distortion of radio signals A transmit radio signal corresponding to an output of a transmitting radio signal processing system is obtained. A pre-distorted radio signal is then generated by processing the transmit radio signal using a nonlinear pre-distortion machine learning model. The nonlinear pre-distortion machine learning model includes model parameters and at least one nonlinear function to correct radio signal distortion or interference. A transmit output radio signal is obtained by processing the pre-distorted radio signal through the transmitting radio signal processing system. The transmit output radio signal is then transmitted to one or more radio receivers.

Abstract: Methods and systems including computer programs encoded on computer storage media, for training and deploying machine-learned communication over RF channels.

Abstract: Methods and systems including computer programs encoded on computer storage media, for training and deploying machine-learned communication over radio frequency (RF) channels. One of the methods includes: determining first information; generating a first RF signal by processing using an encoder machine-learning network; determining a second RF signal that represents the first RF signal altered by transmission through a communication channel; determining a first property of the first signal or the second RF signal; calculating a first measure of distance between a target value of the first property and an actual value of the first or second RF signal; generating second information as a reconstruction of the first information using a decoder machine-learning network; calculating a second measure of distance between the first information and the second information; and updating at least one of the encoder machine-learning network or the decoder machine-learning network based on the first and second measures.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for correcting distortion of radio signals A transmit radio signal corresponding to an output of a transmitting radio signal processing system is obtained. A pre-distorted radio signal is then generated by processing the transmit radio signal using a nonlinear pre-distortion machine learning model. The nonlinear pre-distortion machine learning model includes model parameters and at least one nonlinear function to correct radio signal distortion or interference. A transmit output radio signal is obtained by processing the pre-distorted radio signal through the transmitting radio signal processing system. The transmit output radio signal is then transmitted to one or more radio receivers.

Abstract: Methods and systems including computer programs encoded on computer storage media, for training and deploying machine-learned communication over radio frequency (RF) channels. One of the methods includes: determining first information; generating a first RF signal by processing using an encoder machine-learning network; determining a second RF signal that represents the first RF signal altered by transmission through a communication channel; determining a first property of the first signal or the second RF signal; calculating a first measure of distance between a target value of the first property and an actual value of the first or second RF signal; generating second information as a reconstruction of the first information using a decoder machine-learning network; calculating a second measure of distance between the first information and the second information; and updating at least one of the encoder machine-learning network or the decoder machine-learning network based on the first and second measures.

Abstract: Methods and systems including computer programs encoded on computer storage media, for training and deploying machine-learned communication over radio frequency (RF) channels. One of the methods includes: determining first information; generating a first RF signal by processing using an encoder machine-learning network; determining a second RF signal that represents the first RF signal altered by transmission through a communication channel; determining a first property of the first signal or the second RF signal; calculating a first measure of distance between a target value of the first property and an actual value of the first or second RF signal; generating second information as a reconstruction of the first information using a decoder machine-learning network; calculating a second measure of distance between the first information and the second information; and updating at least one of the encoder machine-learning network or the decoder machine-learning network based on the first and second measures.

Abstract: A computer implemented method and a sales management system (SMS) for generating sales through interactive digital content (IDC) integrate multiple electronic commerce service providers (ECSPs) for facilitating purchase of multiple sale items from within digital media. The SMS preferably inserts an indicator element at a predefined location within the IDC in the digital media that, when activated, invokes a display of multiple sale item indicators. When a sale item indicator is activated, the SMS retrieves sale item information associated with the sale item, and selects an ECSP for completing the purchase of the sale item. The SMS displays a dynamic interactive display element (DIDE) linked to the activated sale item indicator. The DIDE displays sale item information and provides direct purchasing options. The SMS renders a content display interface associated with the selected ECSP based on a selection of one of the purchasing options for initiating purchase of the sale item.

Abstract: A computer implemented method and a sales management system (SMS) for generating sales through interactive digital content (IDC) integrate multiple electronic commerce service providers (ECSPs) for facilitating purchase of multiple sale items from within digital media. The SMS preferably inserts an indicator element at a predefined location within the IDC in the digital media that, when activated, invokes a display of multiple sale item indicators. When a sale item indicator is activated, the SMS retrieves sale item information associated with the sale item, and selects an ECSP for completing the purchase of the sale item. The SMS displays a dynamic interactive display element (DIDE) linked to the activated sale item indicator. The DIDE displays sale item information and provides direct purchasing options. The SMS renders a content display interface associated with the selected ECSP based on a selection of one of the purchasing options for initiating purchase of the sale item.

Abstract: A method and system for providing reliable path for Direct Inward Dial (DID) calls on networks, e.g., Time Division Multiplexed (TDM) networks, the packet networks Voice over Internet Protocol (VoIP) and Service over Internet Protocol (SoIP) networks are disclosed. In one embodiment, the present method enables the customers to request for a reliable path for Direct Inward Dial (DID) calls. For example, the present method enables a service provider to connect a customer's switch, e.g., a PBX, to two or more switches (or softswitches) via two separate DID trunk groups. The method also enables the service provider to create a DID trunk group between the two or more switches (or softswitches) connected to the customer's switch. With this architecture, the service provider is able to continue to forward DID calls towards the customer's switch even if one of the two separate DID trunk groups has failed.

Abstract: A drop floor for a mobile home or a park model home creates additional space and headroom between the ceiling and floor. A home built according to the invention typically includes a frame supported upon an axle. The frame has numerous cross members extending between a pair of opposite side members and includes a first portion located at a first height with respect to the axle and a second portion located at a second height below the first height. A building structure is supported on the first and second frame portions. The invention includes a drop floor construction method where floor decking is attached to the second portion of the frame so that the floor decking is in contact with the frame and located at the second height, which is below the first height. The drop floor includes nailers, closure material and insulation so that the drop floor can rest upon the ground surface if desired.

Abstract: A material-removal system can include a spray-head assembly with a plurality of rotatable fluid bars arranged in a single shroud with overlapping sweeps. A gear-box assembly can index the rotations of the fluid bars to coordinate their rotation and prevent the fluid bars from interfering with one another. The material-removal system can be mounted on a mobile platform, such as a vehicle. The vehicle can have a fluid-storage tank and a debris tank that can be tilted for dumping operation while the fluid-storage tank remains stationary. A peristaltic pump can advantageously remove liquid waste from the debris tank while a vacuum system has the debris tank operating under vacuum. The spray-head assembly can be coupled to the vehicle with an articulating-arm assembly that can include a four-bar mechanism and a pair of rotary actuators to facilitate vertical and rotational movement of the arm assembly and the spray-head assembly.