Micron technology, inc. (20240312530). Classification of Error Rate of Data Retrieved from Memory Cells simplified abstract
Contents
Classification of Error Rate of Data Retrieved from Memory Cells
Organization Name
Inventor(s)
Sivagnanam Parthasarathy of Carlsbad CA (US)
James Fitzpatrick of Laguna Niguel CA (US)
Patrick Robert Khayat of San Diego CA (US)
AbdelHakim S. Alhussien of San Jose CA (US)
Classification of Error Rate of Data Retrieved from Memory Cells - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240312530 titled 'Classification of Error Rate of Data Retrieved from Memory Cells
The abstract describes a memory sub-system that measures signal and noise characteristics of memory cells, determines optimized read voltages, generates features from these characteristics, classifies bit error rates, and controls memory cell operations based on the classification.
- Measures signal and noise characteristics of memory cells
- Determines optimized read voltages for memory cells
- Generates features from signal and noise characteristics
- Classifies bit error rates of data retrievable from memory cells
- Controls memory cell operations based on classification
Potential Applications: - Memory devices - Data storage systems - Error correction technologies
Problems Solved: - Improving data retrieval accuracy - Enhancing memory cell performance - Optimizing read voltages for memory cells
Benefits: - Increased data reliability - Enhanced memory system efficiency - Improved overall performance
Commercial Applications: Title: "Advanced Memory Sub-System for Enhanced Data Retrieval" This technology can be utilized in various industries such as data storage, cloud computing, and telecommunications to improve data retrieval accuracy and system performance.
Prior Art: Researchers can explore existing patents related to memory systems, error correction techniques, and data storage technologies to understand the evolution of similar innovations in the field.
Frequently Updated Research: Stay updated on advancements in memory sub-systems, error correction algorithms, and data storage technologies to incorporate the latest developments into this innovative memory sub-system.
Questions about Memory Sub-System: 1. How does the memory sub-system improve data retrieval accuracy? The memory sub-system measures signal and noise characteristics, determines optimized read voltages, and classifies bit error rates to enhance data retrieval accuracy.
2. What are the potential commercial applications of this memory sub-system? This technology can be applied in various industries such as data storage, cloud computing, and telecommunications to optimize data retrieval and system performance.
Original Abstract Submitted
a memory sub-system configured to: measure a plurality of sets of signal and noise characteristics of a group of memory cells in a memory device; determine a plurality of optimized read voltages of the group of memory cells from the plurality of sets of signal and noise characteristics respectively; generate features from the plurality of sets of signal and noise characteristics, including at least one compound feature generated from the plurality of sets of signal and noise characteristics; generate, using the features, a classification of a bit error rate of data retrievable from the group of memory cells; and control an operation to read the group of memory cells based on the classification.
