ML Anthology

On the Design of BSB Neural Associative Memories Using Semidefinite Programming

Jooyoung Park, Hyuk Cho, Daihee Park
NeCo 1999 pp. 1985-1994
doi:10.1162/089976699300016052 /neco/1999/park1999neco-design/

Abstract

This article is concerned with the reliable search for optimally performing BSB (brain state in a box) neural associative memories given a set of prototype patterns to be stored as stable equilibrium points. By converting and/or modifying the nonlinear constraints of a known formulation for the synthesis of BSB-based associative memories into linear matrix inequalities, we recast the synthesis into semidefinite programming problems and solve them by recently developed interior point methods. The validity of this approach is illustrated by a design example.

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Text

Park et al. "On the Design of BSB Neural Associative Memories Using Semidefinite Programming." Neural Computation, 1999. doi:10.1162/089976699300016052

Markdown

[Park et al. "On the Design of BSB Neural Associative Memories Using Semidefinite Programming." Neural Computation, 1999.](https://mlanthology.org/neco/1999/park1999neco-design/) doi:10.1162/089976699300016052

BibTeX

@article{park1999neco-design,
  title     = {{On the Design of BSB Neural Associative Memories Using Semidefinite Programming}},
  author    = {Park, Jooyoung and Cho, Hyuk and Park, Daihee},
  journal   = {Neural Computation},
  year      = {1999},
  pages     = {1985-1994},
  doi       = {10.1162/089976699300016052},
  volume    = {11},
  url       = {https://mlanthology.org/neco/1999/park1999neco-design/}
}