Pattern Recognition with Networks of Memory Elements

  • I. Aleksander

Abstract

This chapter deals with a development of ideas stemming from the early work of Bledsoe and Browning (1959) in which a binary pattern field was broken up into several randomly selected sets of n binary points called n-tuples. The scheme is adaptive and requires a set of patterns with which the system can be trained: the training set.

Keywords

Radar Retina Assure Mete 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Aleksander, I., 1971, Microcircuit Learning Computers, Mills and Boon, London.Google Scholar
  2. Aleksander, I., 1974, Action-oriented learning networks, Kybernetes, 4: 39–44.CrossRefGoogle Scholar
  3. Aleksander, I., Stonham, T. J., and Wilson, M. J. D., 1974, Adaptive logic for artificially intelligent systems, Radio Electron. Engr., 44: 39–44.CrossRefGoogle Scholar
  4. Bledsoe, W., and Browning, P., 1959, Pattern recognition and reading by machine, Proc. Eastern Joint Computer Conf., p. 225 American Federation of Information Processing Science, Academic Press, New York.Google Scholar
  5. Fairhurst, M. C., and Aleksander, I., 1972, Dynamics of the perception of patterns in random learning nets. In: Machine Perception of Pictures and Patterns, The Physical Society, London.Google Scholar
  6. Minsky, M., and Papert, S., 1969, Perceptions, MIT Press, Cambridge, Mass.Google Scholar
  7. Rosenblatt, F., 1962, Principles of Neurodynamics, Spartan Books, New York.Google Scholar
  8. Stonham, T. J., Aleksander, I., Camp, M., Shaw, M. A., and Pike, W. T., 1973, Automatic classification of mass spectra by means of digital learning nets, Electron Lett., 9:No. 17.Google Scholar

Copyright information

© Plenum Press, New York 1978

Authors and Affiliations

  • I. Aleksander
    • 1
  1. 1.Department of Electronic and Electrical EngineeringBrunei UniversityUxbridge, MiddlesexEngland

Personalised recommendations