Capacity of oscillatory associative-memory networks with error-free retrieval

Takashi Nishikawa, Ying-Cheng Lai, Frank C. Hoppensteadt

Research output: Contribution to journalArticlepeer-review

54 Citations (Scopus)


Networks of coupled periodic oscillators (similar to the Kuramoto model) have been proposed as models of associative memory. However, error-free retrieval states of such oscillatory networks are typically unstable, resulting in a near zero capacity. This puts the networks at disadvantage as compared with the classical Hopfield network. Here we propose a simple remedy for this undesirable property and show rigorously that the error-free capacity of our oscillatory, associative-memory networks can be made as high as that of the Hopfield network. They can thus not only provide insights into the origin of biological memory, but can also be potentially useful for applications in information science and engineering.

Original languageEnglish
Article number108101
Number of pages4
JournalPhysical Review Letters
Issue number10
Publication statusPublished - 12 Mar 2004


  • neural network
  • natural frequencies
  • synchronization
  • patterns
  • cortex
  • model


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