Computational Mechanisms of Pulse-Coupled Neural Networks: A Comprehensive Review

Publication Type:
Journal Article
Citation:
Archives of Computational Methods in Engineering, 2017, 24 (3), pp. 573 - 588
Issue Date:
2017-07-01
Full metadata record
Files in This Item:
Filename Description Size
Zhan2017_Article_ComputationalMechanismsOfPulse.pdfPublished Version1.84 MB
Adobe PDF
© 2016, CIMNE, Barcelona, Spain. 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.
Please use this identifier to cite or link to this item: