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Pattern Recognition in a Bucket

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Advances in Artificial Life (ECAL 2003)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2801))

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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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© 2003 Springer-Verlag Berlin Heidelberg

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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. https://doi.org/10.1007/978-3-540-39432-7_63

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  • DOI: https://doi.org/10.1007/978-3-540-39432-7_63

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-20057-4

  • Online ISBN: 978-3-540-39432-7

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