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A Subgraph Isomorphism Algorithm Based on Hopfield Neural Network

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Advances in Neural Networks – ISNN 2004 (ISNN 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3173))

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Abstract

A subgraph isomorphism algorithm using 2D continuous Hopfield neural network is presented in this paper. Given two graphs G 1 and G 2, the goal is to find a subgraph of G 2 isomorphic to G 1. The rows of the 2D neuron array represent the vertices of G 1, and the columns represent those of G 2. The energy function is defined. The network parameters are deduced from the energy function. The neurons are initialized based on the necessary conditions for subgraph isomorphism. The motion equation is solved using the fourth order Runge-Kutta method. Experimental results show the correctness and validity of the algorithm.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Dalian University of Technology, Dalian, 116023, China

    Ensheng Yu

  2. Department of Engineering Mechanics, Dalian University of Technology, Dalian, 116023, China

    Xicheng Wang

  3. State Key Laboratory of Analysis for Industrial Equipment, Dalian University of Technology, Dalian, 116023, China

    Xicheng Wang

Authors
  1. Ensheng Yu
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  2. Xicheng Wang
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Editor information

Editors and Affiliations

  1. School of Electronic and Information Engineering, Dalian University of Technology, 116023, Dalian, China

    Fu-Liang Yin

  2. Department of Mechanical and Automation Engineering, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China

    Jun Wang

  3. School of Electronic and Information Engineering, Dalian University of Technology, 116023, Dalian, Liaoning, China

    Chengan Guo

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© 2004 Springer-Verlag Berlin Heidelberg

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Yu, E., Wang, X. (2004). A Subgraph Isomorphism Algorithm Based on Hopfield Neural Network. In: Yin, FL., Wang, J., Guo, C. (eds) Advances in Neural Networks – ISNN 2004. ISNN 2004. Lecture Notes in Computer Science, vol 3173. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-28647-9_73

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  • DOI: https://doi.org/10.1007/978-3-540-28647-9_73

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22841-7

  • Online ISBN: 978-3-540-28647-9

  • eBook Packages: Springer Book Archive

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