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Computational Mechanisms of Pulse-Coupled Neural Networks: A Comprehensive Review
This project forked from kunzhan/pulse-coupled_neural_networks_pcnn
Computational Mechanisms of Pulse-Coupled Neural Networks: A Comprehensive Review
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. Many examples of processing mechanisms are provided to make it clear and concise. figure_2.m --- The PCNN 1-D demo figure_4.m --- The PCNN wave demo figure_6.m --- The Image Histogram demo figure_7.m --- The Image Segmentation demo figure_8.m --- The Feature Extraction demo figure_9.m --- The Image Enhancement demo Algorithm_6.m --- image de-noising / restoration demo We appreciate it if you cite the following paper: @Article{zhan2017computational, author = {Zhan, K and Shi, J and Wang, H and Xie, Y and Li, Q}, title = {Computational Mechanisms of Pulse-Coupled Neural Networks: A Comprehensive Review}, journal = {Archives of Computational Methods in Engineering}, year = {2017}, volume = {24}, number = {3}, pages = {573--588}, doi = {10.1007/s11831-016-9182-3}, publisher = {Springer} } http://www.escience.cn/people/kzhan If you have any questions on PCNN, Feel free to contact me. (Email: ice.echo#gmail.com)
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