Literature DB >> 15089247

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

Takashi Nishikawa1, Ying-Cheng Lai, Frank C Hoppensteadt.   

Abstract

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.

Mesh:

Year:  2004        PMID: 15089247     DOI: 10.1103/PhysRevLett.92.108101

Source DB:  PubMed          Journal:  Phys Rev Lett        ISSN: 0031-9007            Impact factor:   9.161


  3 in total

1.  Realistic control of network dynamics.

Authors:  Sean P Cornelius; William L Kath; Adilson E Motter
Journal:  Nat Commun       Date:  2013       Impact factor: 14.919

2.  Decoding Network Structure in On-Chip Integrated Flow Cells with Synchronization of Electrochemical Oscillators.

Authors:  Yanxin Jia; István Z Kiss
Journal:  Sci Rep       Date:  2017-04-07       Impact factor: 4.379

3.  Coupled VO2 Oscillators Circuit as Analog First Layer Filter in Convolutional Neural Networks.

Authors:  Elisabetta Corti; Joaquin Antonio Cornejo Jimenez; Kham M Niang; John Robertson; Kirsten E Moselund; Bernd Gotsmann; Adrian M Ionescu; Siegfried Karg
Journal:  Front Neurosci       Date:  2021-02-11       Impact factor: 4.677

  3 in total

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