Set partition of real numbers by hopfield neural network

Yutaka Hisanaga, Masafumi Yamashita, Tadashi Ae

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


The Hopfield neural network is attracting attention as a high‐speed solver for optimization and other problems. However, it contains a problem in that the network may not arrive at the globally optimal solution but stops at a locally optimal solution unless the initial state is selected appropriately. In other words, the selection of the initial state is important in solving a problem using the Hopfield neural network. This paper considers the real number partition problem, the problem of finding the k largest elements from a given set of real numbers, given integer k. A network to solve this problem is constructed. It is shown that the network arrives at the globally optimal solution if the initial state satisfies a certain condition. Its basin also is examined. As an application example of the network, the sorting problem is considered.

Original languageEnglish
Pages (from-to)88-95
Number of pages8
JournalSystems and Computers in Japan
Issue number10
Publication statusPublished - 1991
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Information Systems
  • Hardware and Architecture
  • Computational Theory and Mathematics


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