A new method of morphological associative memories

  • Authors:

  • Naiqin Feng;Xizheng Cao;Sujuan Li;Lianhui Ao;Shuangxi Wang

  • Affiliations:

  • College of Computer & Information Technology, Henan Normal University, Xinxiang, China;College of Computer & Information Technology, Henan Normal University, Xinxiang, China;College of Computer & Information Technology, Henan Normal University, Xinxiang, China;College of Computer & Information Technology, Henan Normal University, Xinxiang, China;College of Computer & Information Technology, Henan Normal University, Xinxiang, China

  • Venue:
  • ICIC'09 Proceedings of the Intelligent computing 5th international conference on Emerging intelligent computing technology and applications
  • Year:
  • 2009

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Abstract

The morphological associative memories (MAM) have many attractive advantages. However, they can not give a guarantee that morphological hetero-associative memories are perfect, even if input patterns are perfect. In addition, the problem with the associative memory matrixes WXY and MXY is that WXY is incapable of handling dilative noise while MXY is incapable of effectively handling erosive noise. In this paper, the new methods of MAM, +WXY and +MXY are proposed. The certain qualifications that make +WXY and +MXY be perfect memories are analyzed and proved. As far as the hetero-associative memories are concerned, although +WXY and +MXY are not perfect, they are complements to original WXY and MXY. +WXY is capable of handling dilative noise while +MXY is capable of effectively handling erosive noise. Therefore they can be put together with original WXY and MXY to learn from others' strong points to offset ones' own weakness and to make the effect of heteroassociative memories and pattern recognition better. The calculation results demonstrate that both +WXY and +MXY are effectual.