DocumentCode
2714096
Title
A Hybrid Flow for Memory Failure Bitmap Classification
Author
Li, Jianbo ; Huang, Yu ; Cheng, Wu-Tung ; Schuermyer, Chris ; Xiang, Dong ; Faehn, Eric ; Farrugia, Ruth
fYear
2012
fDate
19-22 Nov. 2012
Firstpage
314
Lastpage
319
Abstract
Failure bitmaps of manufactured memory arrays may contain the information of some systematic defects and have hence been used to monitor the process and to improve the memory yield. It is important to have an accurate flow to classify the memory failure bitmap signatures. The memory bitmap signature classification can be either dictionary based or machine learning based. This paper introduces a hybrid flow that can combine dictionary based and machine learning based methods. The proposed method can enhance the accuracy of signature classification, and more importantly, it has the capability of learning new memory bitmap signatures unseen before.
Keywords
learning (artificial intelligence); storage management; hybrid flow; machine learning; memory arrays; memory bitmap signature classification; memory failure bitmap classification; memory failure bitmap signatures; memory yield; Artificial neural networks; Dictionaries; Neurons; Shape; Support vector machine classification; Training; Vectors; Artificial Neural Network (ANN); Dictionary Based Pattern Matching; Machine Learning; Memory Failure Bitmaps; Memory Test;
fLanguage
English
Publisher
ieee
Conference_Titel
Test Symposium (ATS), 2012 IEEE 21st Asian
Conference_Location
Niigata
ISSN
1081-7735
Print_ISBN
978-1-4673-4555-2
Electronic_ISBN
1081-7735
Type
conf
DOI
10.1109/ATS.2012.16
Filename
6394222
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