An oscillatory neural network (ONN) is an artificial neural network that uses coupled oscillators as neurons. Oscillatory neural networks are closely linked to the Kuramoto model, and are inspired by the phenomenon of neural oscillations in the brain. Oscillatory neural networks have been trained to recognize images.[1] Complex-Valued Oscillatory network has also been shown to store and retrieve multidimensional aperiodic signals. [2] An oscillatory autoencoder has also been demonstrated, which uses a combination of oscillators and rate-coded neurons.[3]

A neuron made of two coupled oscillators, one having a fixed and the other having a tunable natural frequency, has been shown able to run logic gates such as XOR that conventional sigmoid neurons cannot. [4]

References

  1. ↑ "Physicists train the oscillatory neural network to recognize images".
  2. ↑ Biswas, Dipayan; Pallikkulath, Sooryakiran; Chakravarthy, V. Srinivasa (2021). "A Complex-Valued Oscillatory Neural Network for Storage and Retrieval of Multidimensional Aperiodic Signals". Frontiers in Computational Neuroscience. 15. doi:10.3389/fncom.2021.551111. PMC 8181409. PMID 34108869.
  3. ↑ Soman, Karthik; Muralidharan, Vignesh; Chakravarthy, V. Srinivasa (2018). "An Oscillatory Neural Autoencoder Based on Frequency Modulation and Multiplexing". Frontiers in Computational Neuroscience. 12: 52. doi:10.3389/fncom.2018.00052. PMC 6048285. PMID 30042669.
  4. ↑ "A Neural Network Based on Synchronized Pairs of Nano-Oscillators".
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