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公开(公告)号:US11836572B2
公开(公告)日:2023-12-05
申请号:US17031501
申请日:2020-09-24
Applicant: QUALCOMM Incorporated
Inventor: Roberto Bondesan , Max Welling
Abstract: Certain aspects of the present disclosure provide a method for performing quantum convolution, including: receiving input data at a neural network model, wherein the neural network model comprises at least one quantum convolutional layer; performing quantum convolution on the input data using the at least one quantum convolutional layer; generating an output wave function based on the quantum convolution using the at least one quantum convolution layer; generating a marginal probability distribution based on the output wave function; and generating an inference based on the marginal probability distribution.
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公开(公告)号:US12199705B2
公开(公告)日:2025-01-14
申请号:US18155454
申请日:2023-01-17
Applicant: QUALCOMM Incorporated
Inventor: Markus Peschl , Daniel Ernest Worrall , Arash Behboodi , Roberto Bondesan , Pouriya Sadeghi , Sanaz Barghi
IPC: H04B7/0456 , H04B7/06 , H04B17/336
Abstract: Certain aspects of the present disclosure provide techniques and apparatus for demapping a signal to a point in a signal constellation. An example method generally includes identifying a seed point in a signal constellation from a received signal. A candidate set of codes for the signal is generated based on a seed point and an additive perturbation applied to the seed point. A point in the signal constellation corresponding to the value of the received signal is identified based on a probability distribution generated over the candidate set of codes. Generally, the identified point corresponds to a code in the candidate set of codes having a highest probability in the probability distribution. The point in the signal constellation is output as the value of the received signal.
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