Advances in Artificial Life

Volume 2801 of the series Lecture Notes in Computer Science pp 588-597

Pattern Recognition in a Bucket

  • Chrisantha FernandoAffiliated withSchool of Cognitive and Computer Sciences, University of Sussex
  • , Sampsa SojakkaAffiliated withSchool of Cognitive and Computer Sciences, University of Sussex

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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.