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A Method to Improve Performance of Heteroassociative Morphological Memories

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Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence (ICIC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 6839))

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Abstract

General speaking, the heteroassociative morphological memory (HMM) is incomplete, namely, it cannot give a guarantee of perfect recall memory, even though without any input noises. The paper focuses on the problem and proposes a new method to improve performance of heteroassociative morphological memories. This method can realize the perfect recall of HMMs for perfect inputs or within a certain range of noises. An example is provided to illustrate the proposed method and its performance.

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References

  1. Davidson, J.L., Ritter, G.X.: Theory of Morphological Neural Networks. In: Digital Optical Computing II, Los Angeles. Proc. SPIE, vol. 1215, pp. 378–388 (1990)

    Google Scholar 

  2. Ritter, G.X., Sussner, P., Diaz-de-Leon, J.L.: Morphological Associative Memories. IEEE Transactions on Neural Networks 9(2), 281–293 (1998)

    Article  Google Scholar 

  3. Chen, S.C., Liu, W.L.: Complex Morphological Associative Memories and Their Performance Analysis. Journal of Software 13(3), 453–459 (2002) (in Chinese)

    Google Scholar 

  4. Wang, M., Wang, S.T., Wu, X.J.: Initial Results on Fuzzy Morphological Associative Memories. Acta Electronica Sinica 31(5), 690–693 (2003) (in Chinese)

    Google Scholar 

  5. Wang, M., Chen, S.C.: Enhanced FMAM Based on Empirical Kernel Map. IEEE Transactions on Neural Networks 16(3), 557–564 (2005)

    Article  Google Scholar 

  6. Feng, N.Q., Qiu, Y.H., Wang, F., Sun, Y.Q.: A Unified Framework of Morphological Associative Memories. In: Huang, D.S., Li, K., Irwin, G.W. (eds.) Proc. 2nd International Conference on Intelligent Computing. CCIS, vol. 344, pp. 1–11. Springer, Heidelberg (2006)

    Google Scholar 

  7. Feng, N.Q., Liu, C.H., Zhang, C.P., et al.: Research on the Framework of Morphological Associative Memories. Chinese Journal of Computers 33(1), 157–166 (2010)

    Article  Google Scholar 

  8. Feng, N.Q., Cao, X.Z., Li, S.J., Ao, L.H., Wang, S.-X.: A New Method of Morphological Associative Memories. In: Huang, D.-S., Jo, K.-H., Lee, H.-H., Kang, H.-J., Bevilacqua, V. (eds.) ICIC 2009. LNCS (LNAI), vol. 5755, pp. 407–416. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  9. Sussner, P.: New Results on Binary Auto- and Heteroassociative Morphological Memories. In: Proceedings of the International Joint Conference on Neural Networks, Montreal, Canada, pp. 1199–1204 (2005)

    Google Scholar 

  10. Vázquez, R.A., Sossa, H.: Morphological Hetero-Associative Memories Applied to Restore True-Color Patterns. In: Yu, W., He, H., Zhang, N. (eds.) ISNN 2009. LNCS, vol. 5553, pp. 520–529. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

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Author information

Authors and Affiliations

  1. College of Computer & Information Technology, Henan Normal University, 453007, Xinxiang, China

    Naiqin Feng, Yushan Zhang, Lianhui Ao & Shuangxi Wang

Authors
  1. Naiqin Feng
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  2. Yushan Zhang
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  3. Lianhui Ao
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  4. Shuangxi Wang
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Computer and Communication Engineering, Zhengzhou University of Light Industry, No. 5, Dongfeng Road, Jinshui District, 450002, Zhengzhou, Henan, China

    Yong Gan

  3. Indian Institute of Technology Kanpur, 208016, Kanpur, India

    Phalguni Gupta

  4. Department of Biotechnology, Indian Institute of Technology Madras, 600 036, Chennai, Tamilnadu, India

    M. Michael Gromiha

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© 2012 Springer-Verlag Berlin Heidelberg

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Feng, N., Zhang, Y., Ao, L., Wang, S. (2012). A Method to Improve Performance of Heteroassociative Morphological Memories. In: Huang, DS., Gan, Y., Gupta, P., Gromiha, M.M. (eds) Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence. ICIC 2011. Lecture Notes in Computer Science(), vol 6839. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25944-9_19

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  • DOI: https://doi.org/10.1007/978-3-642-25944-9_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25943-2

  • Online ISBN: 978-3-642-25944-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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