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Memory capacity and information capacity of sparsely encoded associative memory with replacement units

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Abstract

We introduce sparse encoding into the autoassociative memory model with replacement units. Utilizing computer simulation, we search the optimal number of replacement units in two terms: the memory capacity and the information capacity of the network. We show that the optimal number of replacement units to maximize the memory capacity and the information capacity decreases as the firing ratio decreases, and that the difference in the memory capacity between sparse encoding and non-sparse encoding becomes small as the number of replacement units increases.

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Authors and Affiliations

  1. Graduate School of Engineering and Science, University of the Ryukyus, 1 Senbaru, Nishihara, Okinawa, 903-0213, Japan

    Ryota Miyata

  2. Faculty of Engineering, University of the Ryukyus, Okinawa, Japan

    Shinnosuke Muta & Koji Kurata

Authors
  1. Ryota Miyata
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  2. Shinnosuke Muta
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  3. Koji Kurata
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Corresponding author

Correspondence to Ryota Miyata.

Additional information

This work was presented in part and was awarded the Young Author Award at the 15th International Symposium on Artificial Life and Robotics, Oita, Japan, February 4–6, 2010

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Miyata, R., Muta, S. & Kurata, K. Memory capacity and information capacity of sparsely encoded associative memory with replacement units. Artif Life Robotics 15, 291–295 (2010). https://doi.org/10.1007/s10015-010-0807-6

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  • DOI: https://doi.org/10.1007/s10015-010-0807-6

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