Deep neural network implementation for concatenated codes

    公开(公告)号:US12176924B2

    公开(公告)日:2024-12-24

    申请号:US18184916

    申请日:2023-03-16

    Abstract: Systems, methods, non-transitory computer-readable media configured to perform operations associated with a storage medium. One system includes the storage medium and an encoding/decoding (ED) system, the ED system being configured to receive a set of input log-likelihood ratios (LLRs) of a component of the plurality of components, determine an extrinsic estimation function based on a set of features of the set of input LLRs, analyze the extrinsic estimation function to obtain a plurality of extrinsic LLR values, map the plurality of extrinsic LLR values to an input LLR of the set of input LLRs, and output, for each component, a plurality of updated LLR values based on the mapping.

    DEEP NEURAL NETWORK IMPLEMENTATION FOR CONCATENATED CODES

    公开(公告)号:US20240313806A1

    公开(公告)日:2024-09-19

    申请号:US18184916

    申请日:2023-03-16

    CPC classification number: H03M13/2909 H03M13/1105

    Abstract: Systems, methods, non-transitory computer-readable media configured to perform operations associated with a storage medium. One system includes the storage medium and an encoding/decoding (ED) system, the ED system being configured to receive a set of input log-likelihood ratios (LLRs) of a component of the plurality of components, determine an extrinsic estimation function based on a set of features of the set of input LLRs, analyze the extrinsic estimation function to obtain a plurality of extrinsic LLR values, map the plurality of extrinsic LLR values to an input LLR of the set of input LLRs, and output, for each component, a plurality of updated LLR values based on the mapping.

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