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A Method for the Improvement of the Behavior of Bidirectional Associative Memories as Pattern Classifiers

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Abstract

We present a form of attaining success levels of up to 100% in character classification by the appropriate use of thresholds in the activity functions of the neurons making up the two-layer network with which bidirectional associative memories are implemented, together with a systematic method for generating the weight matrix. The system that is constructed includes a geometrical pre-processing stage that eliminates distortions, thereby improving the results. As a final characteristic, the functioning of the system presents a high level of immunity to noise or deformations. The system was evaluated using the two popular databases NIST#19 and UCI. There was found to be no misclassification in any case, whether under conditions of heavy contamination from noise or distortion of the image to be classified.

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References

  1. Kosko, B.: Bidirectional Associative Memories, IEEE Trans. on Systems, Man and Cybernetics, 18(1) (1988), 49–60.

    Google Scholar 

  2. Wang, Y. F., Cruz, J. B. and Mulligan, J. H.: Two Coding Strategies for Bidirectional Associtive Memory, IEEE Trans. on Neural Networks, 1(1) (1991), 81–82.

    Google Scholar 

  3. Wang, Y. F., Cruz, J. B. and Mulligan, J. H.: Guaranteed Recall of all Training Patterns for Bidirectional Associative Memory, IEEE Trans. on Neural Networks, 2(6) (1991), 559–567.

    Google Scholar 

  4. Wang, Y. F., Cruz, J. B. and Mulligan, J. H.: Multiple Training Concept for Back-Propagation Neural Networks for use in Associative Memories, Neural Networks, 6 (1993), 1169–1175.

    Google Scholar 

  5. Leung, C. S. and Cheung, K. F.: Householder Encoding for Discrete Bidirectional Associative Memory, Proc. of the Intl. Joint Conf. on Neural Networks, IJCNN'91, 1 (1991), 124–137.

    Google Scholar 

  6. Leung, C. S.: Encoding Method for Bidirectional Associative Memory Using Projection on Convex Sets, IEEE Trans. on Neural Networks, 4(5) (1993), 879–881.

    Google Scholar 

  7. Shi, H., Zhao, Y. and Zhuang, X.: A General Model for Bidirectional Associative Memories, IEEE Trans. on System, Man and Cybernetics, 28(4) (1998), 511–519.

    Google Scholar 

  8. Arthithan, G. and Dasgupta, G.: On Problem of Spurious Patterns in Neural Associative Memory Models, IEEE Trans. on Neural Networks, 8(6) (1997), 1483–1491.

    Google Scholar 

  9. Jeng, Y. C. and Teh, C. C.: Modified Intraconnected Bidirectional Associative Memory, IEE Electronic Letters, 27(20) (1998), 1818–1819.

    Google Scholar 

  10. Lee, D. L.: Generalized Intraconnected Bidirectional Associative Memories, IEE Electronic Letters, 34(8) (1998), 736–738.

    Google Scholar 

  11. Heekuck, O. H. and Kothari, S. C.: Adaptation of the Relaxation Method for Learning in Bidirectional Associative Memory, IEEE Trans. on Neural Networks, 5(4) (1994), 576–583.

    Google Scholar 

  12. Simpson, P. K.: Higher-Ordered and Intraconnected Bidirectional Associative Memories, IEEE Trans. on System, Man and Cybernetics 2, 20(3) (1990), 637–653.

    Google Scholar 

  13. Park, J., Kim, H-Y, Park, Y. and Lee, S-W.: A Synthesis procedure for Associative Memories Based on Space-varying Cellular Neural Networks, Neural Networks, 14(1) (2001), 107–113.

    Google Scholar 

  14. Arica, N. and Yarman-Vural, T.: An Overview of Character recognition Focused on Offline Handwriting, IEEE Trans. on Systems, Man and Cybernetics - Part C, 31(2) (2001), 216–233.

    Google Scholar 

  15. Wu, Y. and Pados, D. A.: A Feedforward Bidirectional Associative Memory, IEEE Trans. on Neural Networks, 11(4) (2000), 859–866.

    Google Scholar 

  16. Nadal, J. P. and Toulouse, G.: Information Storage in Sparsely Coded Memory Nets, Networks, 1 (1990), 61–74.

    Google Scholar 

  17. Buckingham, J. and Willshaw, D.: On Setting Unit Thresholds in an Incompletely Connected Associative Net, Networks, 4 (1993), 441–459.

    Google Scholar 

  18. Chua, L. O. and Yang, L.: Cellular Neural Networks: Theory and Applications, IEEE Trans. on Circuits and Systems, 35 (1988), 1257–1290.

    Google Scholar 

  19. Kumar, S.: Memory Anhilitation of Structured Maps in Bidirectional Associative Memories, IEEE Trans. on Neural Networks, 11(4) (2000), 1023–1038.

    Google Scholar 

  20. López-Aligué, F., Alvarez, I., Acevedo, I., Orellana, C. J. and Macías, M. M.: Adaptive BAM for Pattern Classification, Proc. of the Intl. Joint Conf. on Neural Networks, IJCNN'2000, 5 (2000), 529–535.

    Google Scholar 

  21. NIST Special Data Base #19: Image Processing Group. Advanced Systems Division. National Institute of Standards and Technology (1995).

  22. Merz, C. J. and Murphy, P. M.: UCI Repository of Machine Learning Databases (1998). Available at http://www.ics.uci.edu/_mlearn/MLRepository.html

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Authors and Affiliations

  1. Department of Electronics and Electromechanical Engineering, Faculty of Sciences, University of Extremadura, Avda. de Elvas, s/n, 06007, Badajoz, Spain

    Francisco J. López-Aligué, Ignacio Alvarez-Troncoso, M. Isabel Acevedo-Sotoca, Carlos J. García-Orellana & Miguel Macías-Macías

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  1. Francisco J. López-Aligué
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  2. Ignacio Alvarez-Troncoso
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  3. M. Isabel Acevedo-Sotoca
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  4. Carlos J. García-Orellana
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  5. Miguel Macías-Macías
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López-Aligué, F.J., Alvarez-Troncoso, I., Isabel Acevedo-Sotoca, M. et al. A Method for the Improvement of the Behavior of Bidirectional Associative Memories as Pattern Classifiers. Neural Processing Letters 17, 137–148 (2003). https://doi.org/10.1023/A:1023605710549

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