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Handwritten Data Clustering Using Agents Competition in Networks

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Abstract

In this paper, we study a new type of competitive learning scheme realized on large-scale networks. The model consists of several agents walking within the network and competing with each other to occupy as many nodes as possible, while attempting to reject intruder agents. In the end of the process, each agent dominates a community (a strongly connected subnetwork). Here, the model is described by a stochastic dynamical system. In this paper, a mathematical analysis for uncovering the system’s properties is presented. In addition, the model is applied to solve handwritten digits and letters clustering problems. An interesting feature is that the model is able to group the same digits or letters even with considerable distortions into the same cluster. Computer simulations reveal that the proposed technique presents high precision of cluster detections, as well as low computational complexity.

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Acknowledgements

This work is supported by the São Paulo State Research Foundation (FAPESP) and by the Brazilian National Research Council (CNPq).

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Authors and Affiliations

  1. Department of Computer Sciences, Institute of Mathematics and Computer Science (ICMC), University of São Paulo (USP), Av. Trabalhador São-carlense, 400, 13560-970, São Carlos, SP, Brazil

    Thiago C Silva, Liang Zhao & Thiago H. Cupertino

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  1. Thiago C Silva
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  2. Liang Zhao
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  3. Thiago H. Cupertino
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Correspondence to Thiago C Silva.

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C Silva, T., Zhao, L. & Cupertino, T.H. Handwritten Data Clustering Using Agents Competition in Networks. J Math Imaging Vis 45, 264–276 (2013). https://doi.org/10.1007/s10851-012-0353-z

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