Read threshold prediction based on weight-sharing deep neural networks in non-volatile memory devices

Abstract

Devices, systems, and methods for improving the performance of a non-volatile memory are described. An example method includes extracting one or more parameters from each of multiple history reads of a page of the memory device, and processing, using each of multiple first neural networks, a corresponding history read of the multiple history reads to generate a corresponding intermediate vector of multiple intermediate vectors. Each of the multiple first neural networks are trained using measurements from one or more pages of another memory device, and each first neural network is activated upon determining that the one or more parameters for the corresponding history read have been extracted. The method further includes processing, using a second neural network, the multiple intermediate vectors to generate an updated read threshold set, and applying the updated read threshold set to the memory device to retrieve information from the memory device.