Abstract: Systems, devices, and methods related to hybrid basis function, neural network-based digital predistortion (DPD) are provided. An example apparatus for a radio frequency (RF) transceiver includes a digital predistortion (DPD) actuator to receive an input signal associated with a nonlinear component of the RF transceiver and output a predistorted signal. The DPD actuator includes a basis-function-based actuator to perform a first DPD operation using a set of basis functions associated with a first nonlinear characteristic of the nonlinear component. The DPD actuator further includes a neural network-based actuator to perform a second DPD operation using a first neural network associated with a second nonlinear characteristic of the nonlinear component. The predistorted signal is based on a first output signal of the basis-function-based actuator and a second output signal of the neural network-based actuator.

Abstract: Systems, devices, and methods related to hybrid basis function, neural network-based digital predistortion (DPD) are provided. An example apparatus for a radio frequency (RF) transceiver includes a digital predistortion (DPD) actuator to receive an input signal associated with a nonlinear component of the RF transceiver and output a predistorted signal. The DPD actuator includes a basis-function-based actuator to perform a first DPD operation using a set of basis functions associated with a first nonlinear characteristic of the nonlinear component. The DPD actuator further includes a neural network-based actuator to perform a second DPD operation using a first neural network associated with a second nonlinear characteristic of the nonlinear component. The predistorted signal is based on a first output signal of the basis-function-based actuator and a second output signal of the neural network-based actuator.

Abstract: Systems, devices, and methods related to using model architecture search for hardware configuration are provided. A method includes receiving, by a computer-implemented system, information associated with a pool of processing units; receiving, by the computer-implemented system, a data set associated with a data transformation operation; training, based on the data set and the information associated with the pool of processing units, a parameterized model associated with the data transformation operation, where the training includes updating at least one parameter of the parameterized model associated with configuring at least a subset of the processing units in the pool; and outputting, based on the training, one or more configurations for at least the subset of the processing units in the pool.

Abstract: It is not trivial to implement speech and natural language processing in offline embedded systems. Voice control of devices in various settings and applications can benefit from an embedded speech and natural language processing solution. One feature that helps to correct automatic speech recognition outputs is grammar projection. Another feature addresses situations where there is imperfect information or incomplete information by providing an application programming interface to enable structured queries and responses between an interpreter and an application.

Abstract: Systems, devices, and methods related to using model architecture search for hardware configuration are provided. A method includes receiving, by a computer-implemented system, information associated with a pool of processing units; receiving, by the computer-implemented system, a data set associated with a data transformation operation; training, based on the data set and the information associated with the pool of processing units, a parameterized model associated with the data transformation operation, where the training includes updating at least one parameter of the parameterized model associated with configuring at least a subset of the processing units in the pool; and outputting, based on the training, one or more configurations for at least the subset of the processing units in the pool.

Abstract: Systems, devices, and methods related to using model architecture search for hardware configuration are provided. An example apparatus includes an input node to receive an input signal; a pool of processing units to perform one or more arithmetic operations and one or more signal selection operations, wherein each of the processing units in the pool is associated with at least one parameterized model corresponding to a data transformation operation; and a control block to configure, based on a first parameterized model, a first subset of the processing units in the pool, where the first subset of the processing units processes the input signal to generate a first signal.

Abstract: Systems, devices, and methods related to hybrid basis function, neural network-based digital predistortion (DPD) are provided. An example apparatus for a radio frequency (RF) transceiver includes a digital predistortion (DPD) actuator to receive an input signal associated with a nonlinear component of the RF transceiver and output a predistorted signal. The DPD actuator includes a basis-function-based actuator to perform a first DPD operation using a set of basis functions associated with a first nonlinear characteristic of the nonlinear component. The DPD actuator further includes a neural network-based actuator to perform a second DPD operation using a first neural network associated with a second nonlinear characteristic of the nonlinear component. The predistorted signal is based on a first output signal of the basis-function-based actuator and a second output signal of the neural network-based actuator.

Abstract: An electronic device can include a semiconductor material including a channel region configured to conduct a current, a source contact electrically coupled to the channel region at a first location, a drain contact electrically coupled to the channel region at a second location spaced apart from the first location, a partial-polarization material on the semiconductor material between the source contact and the drain contact opposite the channel region and a gate contact on the partial-polarization material opposite the channel region and ohmically coupled to the drain contact or ohmically coupled to the source contact.

Abstract: An electronic device can include a semiconductor material including a channel region configured to conduct a current, a source contact electrically coupled to the channel region at a first location, a drain contact electrically coupled to the channel region at a second location spaced apart from the first location, a partial-polarization material on the semiconductor material between the source contact and the drain contact opposite the channel region and a gate contact on the partial-polarization material opposite the channel region and ohmically coupled to the drain contact or ohmically coupled to the source contact.