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Computational mechanisms of pulse-coupled neural networks: a comprehensive review. (English) Zbl 1375.92006

Summary: Pulse-coupled neural networks (PCNN) have an inherent ability to process the signals associated with the digital visual images because it is inspired from the neuronal activity in the primary visual area, V1, of the neocortex. This paper provides insight into the internal operations and behaviors of PCNN, and reveals the way how PCNN achieves good performance in digital image processing. The various properties of PCNN are categorized into a novel three-dimensional taxonomy for image processing mechanisms. The first dimension specifies the time matrix of PCNN, the second dimension captures the firing rate of PCNN, and the third dimension is the synchronization of PCNN. Many examples of processing mechanisms are provided to make it clear and concise.

MSC:

92B20 Neural networks for/in biological studies, artificial life and related topics
62M45 Neural nets and related approaches to inference from stochastic processes
62H35 Image analysis in multivariate analysis

Software:

mgconvert.py; Python
Full Text: DOI

References:

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