Invention Grant
- Patent Title: Decoders and systems for decoding encoded data using neural networks
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Application No.: US17302226Application Date: 2021-04-27
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Publication No.: US11973513B2Publication Date: 2024-04-30
- Inventor: Fa-Long Luo , Jaime Cummins
- Applicant: MICRON TECHNOLOGY, INC.
- Applicant Address: US ID Boise
- Assignee: Micron Technology, Inc.
- Current Assignee: Micron Technology, Inc.
- Current Assignee Address: US ID Boise
- Agency: Dorsey & Whitney LLP
- Main IPC: G06F11/00
- IPC: G06F11/00 ; G06N3/049 ; G06N3/08 ; H03M13/01 ; H03M13/11 ; H03M13/13

Abstract:
Examples described herein utilize multi-layer neural networks, such as multi-layer recurrent neural networks to estimate message probability compute data based on encoded data (e.g., data encoded using one or more encoding techniques). The neural networks and/or recurrent neural networks may have nonlinear mapping and distributed processing capabilities which may be advantageous in many systems employing a neural network or recurrent neural network to estimate message probability compute data for a message probability compute (MPC) decoder. In this manner, neural networks or recurrent neural networks described herein may be used to implement aspects of error correction coding (ECC) decoders, e.g., an MPC decoder that iteratively decodes encoded data.
Public/Granted literature
- US20220368349A1 DECODERS AND SYSTEMS FOR DECODING ENCODED DATA USING NEURAL NETWORKS Public/Granted day:2022-11-17
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