Abstract
This paper presents a new diffusion and growing neural network model called DGSOM for self-organization, where more generalized ideas of short-range competition and long-range cooperation are adopted while introducing the diffusion mechanism of intrinsic NO as its most remarkable characteristic. The new DGSOM model can compartmentalize input space rationally and efficiently, and generated topological connections among neurons can reflect the dimensionality and structure of input signals. Experiments and simulations indicated that the embedding of NO diffusion mechanism improve the performance of self-organization remarkably, especially the flexibility and rapidity of response for dynamic distribution.
Supported by Natural Science Foundation of China (60171003), the Distinguished Young Scholars Fund of China (60225015), Ministry of Science and Technology of China(2001CCA04100) and Ministry of Education of China (TRAPOYT Project).
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Chen, S., Zhou, Z., Hu, D. (2004). Diffusion and Growing Self-Organizing Map: A Nitric Oxide Based Neural Model. 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_34
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DOI: https://doi.org/10.1007/978-3-540-28647-9_34
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-22841-7
Online ISBN: 978-3-540-28647-9
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