Skip to main content
Log in

The time-into-intensity-mapping network

  • Published:
Biological Cybernetics Aims and scope Submit manuscript

Abstract

We employ a special combination of different networks in order to process (transient) spatiotemporal patterns. In a first layer, feature analyzing cells translate instantaneous spatial patterns into activities of cells symbolizing the presence of certain feature values. A second layer maps the time sequence of symbols into a spatial activity pattern of the so-called TIM-cells. A third layer recognizes predefined activity patterns. We demonstrate the behaviour of the network using gaussian patterns in (1 + 1) space-time dimensions.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

References

  • Banzhaf W (1991) Processing spatio-temporal patterns by mapping time into intensity. In: Proc IJCNN Seattle 1991 11:871–877

    Google Scholar 

  • Banzhaf W, Haken H (1990) Learning in a competitive network. Neural Networks 3:421–435

    Google Scholar 

  • Cohen MA, Grossberg S (1987) Masking fields: a massively parallel architecture for learning, recognizing, and predicting multiple groupings of patterned data. Appl Opt 26:1866–1891

    Google Scholar 

  • Haken H (1987) Synergetic computers for pattern recognition and associative memory. In: Haken H (ed) Computational systems, natural and artificial. Proceedings of the Elmau International Symposium on Synergetics 1987. Springer, Berlin Heidelberg New York, pp 1–21

    Google Scholar 

  • Haken H (1988) Nonequilibrium phase transitions in pattern recognition and associative memory. Z Phys B-Condensed Matter 70:121–123

    Google Scholar 

  • Hecht-Nielsen R (1987) Nearest matched filter classification of spatiotemporal patterns. Appl Opt 26:1892–1899

    Google Scholar 

  • Nowlan SJ (1990) Maximum likelihood competitive learning. In: Touretzky DS (ed) Advances in neural information processing systems, vol 2. Morgan Kaufmann, San Mateo, Calif pp 574–582

    Google Scholar 

  • Wang D, Arbib M (1990) Complex temporal pattern sequence learning based on short-term memory. Proc IEEE 78:1536–1543

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Banzhaf, W., Kyuma, K. The time-into-intensity-mapping network. Biol. Cybern. 66, 115–121 (1991). https://doi.org/10.1007/BF00243287

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF00243287

Keywords

Navigation