Analog Devices,inc.

Optum, Inc.

Daniel J Mulcahy

Kimo Tam

Stuart John McCracken

Pablo Acosta-Serafini

Kimo Y F Tam

Damian Kelly

Vijay S Nori

Jennifer Lloyd

Adam Russell

William Frederick Ellersick

Christina Winans Burke

Mary Duncan

Zhongjian Liu

Kathrin Bujna

Donald W James

Subhash Seelam

There is a need for more effective and efficient predictive data analysis. This need can be addressed by, for example, solutions for performing/executing hybrid input predictive data analysis. In one example, a method includes identifying a vocabulary data object associated with one or more prediction input text data objects; determining, based at least in part on the vocabulary data object, a per-input-entity tokenized representation for the one or more prediction input text data objects; determining, based at least in part on the per-input-entity tokenized representation and one or more prediction input structured data objects and using a hybrid-input predictive model, a prediction score; determining, based at least in part on one or more threshold determination configuration criteria, a predictive threshold for the hybrid-input predictive model; generating, based at least in part on the prediction score and the predictive threshold, a predictive output; and performing one or more prediction-based actions based at least in part on the predictive output.

Hybrid-input predictive data analysis

There is a need for more effective and efficient information deficiency processing. This need can be addressed by, for example, solutions for performing/executing label-based information deficiency processing. In one example, a method includes receiving a predictive input associated with a predictive entity based on the predictive input; determining a plurality of encoding probability values for the predictive entity based on the predictive input; determining a plurality of attention-based encoding vectors for the predictive entity based on the plurality of encoding probability values; determining an encoding deficiency prediction for the predictive entity, wherein the encoding deficiency prediction indicates a deficient subset of a plurality of encoding designations; and for each encoding designation in the deficient subset, performing a corresponding prediction-based action.

Label-based information deficiency processing

Machine-learning based recommendation engines are configured to execute machine-learning models to generate recommendations as output for a user based at least in part on functional data received at the recommendation engine. The recommendation engine is further configured to automatically determine the relative importance of one or more functional data entries in generating the recommendation. Moreover, the recommendation engine executes additional machine-learning models, including a machine-learning model trained to avoid negative outcomes, and an opportunity-based machine-learning model to identify alternative recommendation options based on alternative training logic.

Machine-learning based recommendation engine providing transparency in generation of recommendations

Apparatus and methods are disclosed, such as those involving a receiver device. One such apparatus includes an equalizer configured to process an input signal transmitted over a channel. The equalizer can include a programmable gain amplifier (PGA) block which includes an input node configured to receive the input signal; an output node; and a programmable gain amplifier (PGA). The PGA amplifies the input signal with an adjustable gain. The PGA block also includes a gain control block having an input electrically coupled to the input node. The gain control block is configured to adjust the gain of the PGA at least partly in response to the input signal from the input node such that the PGA generates an output signal with a substantially constant amplitude envelope to the output node.

Methods for digitally-controlled automatic gain amplification

Apparatus and method for digitally-controlled automatic gain amplification

A method of operating a circuit for processing a digital signal is disclosed. The circuit includes various circuit stages having respective enabled states. A present signal path is established which includes circuit stages in their respective enabled states. Power is disabled to selected circuit stages not used in the present signal path so as to minimize power consumption in the disabled circuit stages. A data signal is then processed through the circuit stages in the present signal path. Before a next signal path is needed, power is re-enabled to selected disabled circuit stages in the next signal path to allow the enabled circuit stages to approach their respective enabled states. Then the next signal path can be established including the enabled circuit stages in their respective enabled states. The data signal can then be processed through the circuit stages in the next signal path.

Crosspoint switch with low reconfiguration latency

A system and method of calibration develops a function from which is generated a monotonic time response; a gating period is defined from the monotonic time response and any error in the frequency of a reference signal is determined during the gating period; from that error an error signal is generated for adjusting the time constant of a circuit to be calibrated.

Calibration method and system that generates an error signal for adjusting the time constant of circuit to be calibrated

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Somerville, MA, United States of America

Daniel J Mulcahy