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1. WO2020139976 - NEURAL NETWORKS AND SYSTEMS FOR DECODING ENCODED DATA

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Publication Number WO/2020/139976
Publication Date 02.07.2020
International Application No. PCT/US2019/068616
International Filing Date 26.12.2019
IPC
G06N 3/04 2006.01
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architecture, e.g. interconnection topology
G06N 3/063 2006.01
GPHYSICS
06COMPUTING; CALCULATING OR COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
06Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
063using electronic means
H03M 13/15 2006.01
HELECTRICITY
03BASIC ELECTRONIC CIRCUITRY
MCODING, DECODING OR CODE CONVERSION, IN GENERAL
13Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
03Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words
05using block codes, i.e. a predetermined number of check bits joined to a predetermined number of information bits
13Linear codes
15Cyclic codes, i.e. cyclic shifts of codewords produce other codewords, e.g. codes defined by a generator polynomial, Bose-Chaudhuri-Hocquenghem codes
H03M 13/11 2006.01
HELECTRICITY
03BASIC ELECTRONIC CIRCUITRY
MCODING, DECODING OR CODE CONVERSION, IN GENERAL
13Coding, decoding or code conversion, for error detection or error correction; Coding theory basic assumptions; Coding bounds; Error probability evaluation methods; Channel models; Simulation or testing of codes
03Error detection or forward error correction by redundancy in data representation, i.e. code words containing more digits than the source words
05using block codes, i.e. a predetermined number of check bits joined to a predetermined number of information bits
11using multiple parity bits
CPC
G06F 17/18
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
FELECTRIC DIGITAL DATA PROCESSING
17Digital computing or data processing equipment or methods, specially adapted for specific functions
10Complex mathematical operations
18for evaluating statistical data ; , e.g. average values, frequency distributions, probability functions, regression analysis
G06K 9/6223
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
9Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
62Methods or arrangements for recognition using electronic means
6217Design or setup of recognition systems and techniques; Extraction of features in feature space; Clustering techniques; Blind source separation
6218Clustering techniques
622Non-hierarchical partitioning techniques
6221based on statistics
6223with a fixed number of clusters, e.g. K-means clustering
G06N 3/0472
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architectures, e.g. interconnection topology
0472using probabilistic elements, e.g. p-rams, stochastic processors
G06N 3/0481
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
04Architectures, e.g. interconnection topology
0481Non-linear activation functions, e.g. sigmoids, thresholds
G06N 3/063
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
06Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons
063using electronic means
G06N 3/08
GPHYSICS
06COMPUTING; CALCULATING; COUNTING
NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
3Computer systems based on biological models
02using neural network models
08Learning methods
Applicants
  • MICRON TECHNOLOGY, INC. [US]/[US]
Inventors
  • LUO, Fa-Long
  • CUMMINS, Jaime
  • SCHMITZ, Tamara
Agents
  • SPAITH, Jennifer
Priority Data
16/233,57627.12.2018US
Publication Language English (EN)
Filing Language English (EN)
Designated States
Title
(EN) NEURAL NETWORKS AND SYSTEMS FOR DECODING ENCODED DATA
(FR) RÉSEAUX NEURONAUX ET SYSTÈMES DE DÉCODAGE DE DONNÉES CODÉES
front page image
Abstract
(EN)
Examples described herein utilize multi-layer neural networks to decode encoded data (e.g., data encoded using one or more encoding techniques). The neural networks may have nonlinear mapping and distributed processing capabilities which may be advantageous in many systems employing the neural network decoders. In this manner, neural networks described herein may be used to implement error code correction (ECC) decoders.
(FR)
L'invention, selon certains exemples, concerne des réseaux neuronaux multicouches servant à décoder des données codées (par exemple, des données codées à l'aide d'une ou de plusieurs techniques de codage). Les réseaux neuronaux peuvent avoir des capacités de mappage non linéaire et de traitement distribué qui peuvent être avantageux dans de nombreux systèmes faisant appel aux décodeurs de réseaux neuronaux. De cette manière, des réseaux neuronaux selon la présente invention peuvent servir à mettre en œuvre des décodeurs de correction de code d'erreur (ECC).
Also published as
US20200210816
US20200234103
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