Pattern Recognition in a Bucket

  • Chrisantha Fernando
  • Sampsa Sojakka
Conference paper

DOI: 10.1007/978-3-540-39432-7_63

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2801)
Cite this paper as:
Fernando C., Sojakka S. (2003) Pattern Recognition in a Bucket. In: Banzhaf W., Ziegler J., Christaller T., Dittrich P., Kim J.T. (eds) Advances in Artificial Life. ECAL 2003. Lecture Notes in Computer Science, vol 2801. Springer, Berlin, Heidelberg

Abstract

This paper demonstrates that the waves produced on the surface of water can be used as the medium for a “Liquid State Machine” that pre-processes inputs so allowing a simple perceptron to solve the XOR problem and undertake speech recognition. Interference between waves allows non-linear parallel computation upon simultaneous sensory inputs. Temporal patterns of stimulation are converted to spatial patterns of water waves upon which a linear discrimination can be made. Whereas Wolfgang Maass’ Liquid State Machine requires fine tuning of the spiking neural network parameters, water has inherent self-organising properties such as strong local interactions, time-dependent spread of activation to distant areas, inherent stability to a wide variety of inputs, and high complexity. Water achieves this “for free”, and does so without the time-consuming computation required by realistic neural models. An analogy is made between water molecules and neurons in a recurrent neural network.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Chrisantha Fernando
    • 1
  • Sampsa Sojakka
    • 1
  1. 1.School of Cognitive and Computer SciencesUniversity of SussexBrightonUK

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