• 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