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Output-threshold coupled neural network for solving the shortest path problems

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Abstract

This paper presents a coupled neural network, called output-threshold coupled neural network (OTCNN), which can mimic the autowaves in the present pulsed coupled neural networks (PCNNs), by the construction of mutual coupling between neuron outputs and the threshold of a neuron. Based on its autowaves, this paper presents a method for finding the shortest path in shortest time with OTCNNs. The method presented here features much fewer neurons needed, simplicity of the structure of the neurons and the networks, and large scale of parallel computation. It is shown that OTCNN is very effective in finding the shortest paths from a single start node to multiple destination nodes for asymmetric weighted graph, with a number of iterations proportional only to the length of the shortest paths, but independent of the complexity of the graph and the total number of existing paths in the graph. Finally, examples for finding the shortest path are presented.

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Authors and Affiliations

  1. Key Lab on Radar Signal Processing, Xidian University, 710071, Xi’an, China

    Zhang Junying

  2. Computer Department, Xi’an Engineering Science and Technology Institute, 710048, Xi’an, China

    Shi Meihong

  3. Institute of Computer Science, Xidian University, 710071, Xi’an, China

    Zhang Junying & Wang Defeng

  4. Department of Electrical and Computer Engineering, Virginia Polytechnic Institute and State University, 22314, Alexandria, VA, USA

    Wang Joseph Yue

Authors
  1. Zhang Junying
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  2. Wang Defeng
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  3. Shi Meihong
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  4. Wang Joseph Yue
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Correspondence to Zhang Junying.

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Zhang, J., Wang, D., Shi, M. et al. Output-threshold coupled neural network for solving the shortest path problems. Sci China Ser F 47, 20–33 (2004). https://doi.org/10.1360/02yf0313

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  • DOI: https://doi.org/10.1360/02yf0313

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