US 12,112,813 B2
Device for determining read reference voltage of a memory device and operating method thereof
Sunyoung Jo, Daejeon (KR); Jungwuk Park, Daejeon (KR); Younghyun Park, Daejeon (KR); Sang Ho Yun, Icheon (KR); and Jaekyun Moon, Daejeon (KR)
Assigned to SK hynix Inc., Icheon (KR); and Korea Advanced Institute of Science and Technology, Daejeon (KR)
Filed by SK hynix Inc., Icheon (KR); and Korea Advanced Institute of Science and Technology, Daejeon (KR)
Filed on Jun. 22, 2022, as Appl. No. 17/847,056.
Claims priority of application No. 10-2022-0013649 (KR), filed on Jan. 28, 2022.
Prior Publication US 2023/0298677 A1, Sep. 21, 2023
Int. Cl. G11C 16/34 (2006.01); G06N 3/045 (2023.01); G11C 16/28 (2006.01)
CPC G11C 16/3431 (2013.01) [G06N 3/045 (2023.01); G11C 16/28 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A device comprising:
a threshold voltage distribution estimation network configured to generate an estimated distribution matrix using a feature distribution matrix and read trial information, the threshold voltage distribution estimation network including a feature distribution generating circuit and a combination circuit, the feature distribution generating circuit configured to generate the feature distribution matrix from a plurality of threshold voltage distributions for a plurality of pages of a memory device, the combination circuit configured to generate the estimation distribution matrix by combining a plurality of vectors included in the feature distribution matrix using a combination coefficient vector; and
a read reference voltage estimation network configured to generate a read reference voltage from the estimated distribution matrix,
wherein the read trial information includes a read trial vector and an output value, the output value being generated by applying the read trial vector to a threshold voltage distribution for a page to be read among the plurality of threshold voltage distributions, and
wherein the threshold voltage distribution estimation network further includes a coefficient estimation network configured to generate the combination coefficient vector from the read trial information.