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MEMORY SYSTEM WITH DEEP LEARNING BASED INTERFERENCE CORRECTION CAPABILITY AND METHOD OF OPERATING SUCH MEMORY SYSTEM

机译:基于深度学习的干扰校正能力的内存系统及其运行方法

摘要

Memory systems, controllers, decoders and methods execute decoding with a mufti-level interference correction scheme. A decoder performs first soft decoding to generate log likelihood ratio (LLR) values of a select bit and bits of memory cells neighboring a memory cell of the select bit. A quantizer obtains an estimated LLR value of the select bit based on the LLR values of the select bit and the bits of the memory cells neighboring the memory cell of the select bit, when the first soft decoding fails. The decoder performs second soft decoding using the estimated LLR value when the first soft decoding fails, and performs third soft decoding using information obtained from application of a deep learning model to provide a more accurate estimate of the LLR value of the select bit when the second soft decoding fails.
机译:存储器系统,控制器,解码器和方法利用多级干扰校正方案执行解码。解码器执行第一软解码以生成选择位和与该选择位的存储单元相邻的存储单元的位的对数似然比(LLR)值。当第一软解码失败时,量化器基于选择位的LLR值和与选择位的存储单元相邻的存储单元的位来获得选择位的估计LLR值。当第一软解码失败时,解码器使用估计的LLR值执行第二软解码;当第二软解码失败时,解码器使用从深度学习模型的应用获得的信息执行第三软解码,以提供选择位的LLR值的更准确估计软解码失败。

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