Abstract: Embodiments of the present invention disclose methods and apparatuses for correcting errors in data stored in a solid state device. The solid state device may have a plurality of bits stored in multi-level memory cells. The method may include identifying one or more errors in a plurality of memory cells. The method may further include converting the erroneous cells to erasures. The method may further include correcting the one or more erasures.

Abstract: Embodiments of the present invention disclose methods and apparatuses for correcting errors in data stored in a solid state device. The solid state device may have a plurality of bits stored in multi-level memory cells. The method may include identifying one or more errors in a plurality of memory cells. The method may further include converting the erroneous cells to erasures. The method may further include correcting the one or more erasures.

Abstract: Apparatuses and methods for read threshold voltage selection are provided. One example method can include setting a first soft read threshold voltage and a second soft read threshold voltage based on a difference between a first number of memory cells that are read as being programmed to a first state when read using a first threshold voltage and a second number of memory that are read as being programmed to the first state when read using another threshold voltage.

Abstract: Embodiments of the present invention disclose methods and apparatuses for correcting errors in data stored in a solid state device. The solid state device may have a plurality of bits stored in multi-level memory cells. The method may include identifying one or more errors in a plurality of memory cells. The method may further include converting the erroneous cells to erasures. The method may further include correcting the one or more erasures.

Abstract: Apparatuses and methods for read threshold voltage selection are provided. One example method can include setting a first soft read threshold voltage and a second soft read threshold voltage based on a difference between a first number of memory cells that are read as being programmed to a first state when read using a first threshold voltage and a second number of memory that are read as being programmed to the first state when read using another threshold voltage.

Abstract: Apparatuses and methods for read threshold voltage selection are provided. One example method can include setting a first soft read threshold voltage and a second soft read threshold voltage based on a difference between a first number of memory cells that are read as being programmed to a first state when read using a first threshold voltage and a second number of memory that are read as being programmed to the first state when read using another threshold voltage.

Abstract: Embodiments of the present invention disclose methods and apparatuses for correcting errors in data stored in a solid state device. The solid state device may have a plurality of bits stored in multi-level memory cells. The method may include identifying one or more errors in a plurality of memory cells. The method may further include converting the erroneous cells to erasures. The method may further include correcting the one or more erasures.

Abstract: Apparatuses and methods for read threshold voltage selection are provided. One example method can include setting a first soft read threshold voltage and a second soft read threshold voltage based on a difference between a first number of memory cells that are read as being programmed to a first state when read using a first threshold voltage and a second number of memory that are read as being programmed to the first state when read using another threshold voltage.

Abstract: Embodiments of the present invention disclose methods and apparatuses for correcting errors in data stored in a solid state device. The solid state device may have a plurality of bits stored in multi-level memory cells. The method may include identifying one or more errors in a plurality of memory cells. The method may further include converting the erroneous cells to erasures. The method may further include correcting the one or more erasures.

Abstract: Apparatuses and methods for read threshold voltage selection are provided. One example method can include setting a first soft read threshold voltage and a second soft read threshold voltage based on a difference between a first number of memory cells that are read as being programmed to a first state when read using a first threshold voltage and a second number of memory that are read as being programmed to the first state when read using another threshold voltage.

Abstract: Apparatuses and methods for soft read threshold location calibration are provided. One example method can include selecting read threshold sets (RTSs), and determining log-likelihood-ratios (LLRs) based on a number of decisions that correspond to each bin associated with the selected RTSs. Low-density parity-check (LDPC) codewords are decoded using the determined LLRs, and a RTS of the RTSs yielding a least number of failed codewords decoded using the determined LLRs is identified.

Abstract: Apparatuses and methods for read threshold voltage selection are provided. One example method can include setting a first soft read threshold voltage and a second soft read threshold voltage based on a difference between a first number of memory cells that are read as being programmed to a first state when read using a first threshold voltage and a second number of memory that are read as being programmed to the first state when read using another threshold voltage.

Abstract: Apparatuses and methods for read threshold voltage selection are provided. One example method can include setting a first soft read threshold voltage and a second soft read threshold voltage based on a difference between a first number of memory cells that are read as being programmed to a first state when read using a first threshold voltage and a second number of memory that are read as being programmed to the first state when read using another threshold voltage.

Abstract: Apparatuses and methods for soft read threshold location calibration are provided. One example method can include selecting read threshold sets (RTSs), and determining log-likelihood-ratios (LLRs) based on a number of decisions that correspond to each bin associated with the selected RTSs. Low-density parity-check (LDPC) codewords are decoded using the determined LLRs, and a RTS of the RTSs yielding a least number of failed codewords decoded using the determined LLRs is identified.

Abstract: Apparatuses and methods for read threshold voltage selection are provided. One example method can include setting a first soft read threshold voltage and a second soft read threshold voltage based on a difference between a first number of memory cells that are read as being programmed to a first state when read using a first threshold voltage and a second number of memory that are read as being programmed to the first state when read using another threshold voltage.

Abstract: The present disclosure includes apparatuses, methods, and non-transitory computer-readable storage mediums for generation and application of gray codes. One example method comprises: selecting a particular N-bit member as a root member for a plurality of N-bit gray codes each comprising X members such that each of the plurality of N-bit gray codes comprise a same root member; and generating X?1 remaining members of the respective plurality of N-bit gray codes by performing X?1 member generation iterations, wherein each ith iteration of the X?1 member generation iterations generates respective ith members of the plurality of N-bit gray codes based on ith?1 members, with each one of the respective ith members comprising only those eligible neighbor members of a respective one of the ith?1 members, and with “i” being a whole number index from 1 to X?1.

Abstract: Apparatuses and methods for soft read threshold location calibration are provided. One example method can include selecting read threshold sets (RTSs), and determining log-likelihood-ratios (LLRs) based on a number of decisions that correspond to each bin associated with the selected RTSs. Low-density parity-check (LDPC) codewords are decoded using the determined LLRs, and a RTS of the RTSs yielding a least number of failed codewords decoded using the determined LLRs is identified.

Abstract: A memory device may include memory components for storing data. The memory device may also include a controller that determines whether one or more errors exist in a data packet stored in the memory components. The controller may read a code word associated with the data packet, such that the code word may be used to indicate whether the errors exist in the data packet. The controller may then determine a syndrome polynomial based on the code word and determine an inverse of the syndrome polynomial when the syndrome polynomial is not zero. The controller may then determine a first error locator polynomial and a second error locator polynomial based on the inverse of the syndrome polynomial. The first error locator polynomial and the second error locator polynomial may be used to identify one or more locations of one or more errors in the code word.

Abstract: Embodiments of the present invention disclose methods and apparatuses for correcting errors in data stored in a solid state device. The solid state device may have a plurality of bits stored in multi-level memory cells. The method may include identifying one or more errors in a plurality of memory cells. The method may further include converting the erroneous cells to erasures. The method may further include correcting the one or more erasures.

Abstract: The present disclosure includes methods and apparatuses for mapping between program states and data patterns. One method includes mapping a data pattern to a number of program state combinations L corresponding to a group of memory cells configured to store a fractional number of data units per cell. The mapping can be based, at least partially, on a recursive expression performed in a number of operations, the number of operations based on a number of memory cells N within the group of memory cells and the number of program state combinations L.