A New Multivalued Neural Network for Isomorphism Identification of Kinematic Chains

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  • Gloria Galán-Marín
    Department of Mechanical, Energetic and Materials Engineering, University of Extremadura, Avda. de Elvas s/n; 06006 Badajoz, Spain
  • Domingo López-Rodríguez
    Department of Applied Mathematics, University of Malaga, Campus de Teatinos s/n; 29071 Malaga, Spain
  • Enrique Mérida-Casermeiro
    Department of Applied Mathematics, University of Malaga, Campus de Teatinos s/n; 29071 Malaga, Spain

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<jats:p>A lot of methods have been proposed for the kinematic chain isomorphism problem. However, the tool is still needed in building intelligent systems for product design and manufacturing. In this paper, we design a novel multivalued neural network that enables a simplified formulation of the graph isomorphism problem. In order to improve the performance of the model, an additional constraint on the degree of paired vertices is imposed. The resulting discrete neural algorithm converges rapidly under any set of initial conditions and does not need parameter tuning. Simulation results show that the proposed multivalued neural network performs better than other recently presented approaches.</jats:p>

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