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VLSISP
2002

Image processing using cellular neural networks based on multi-valued and universal binary neurons

13 years 11 months ago
Image processing using cellular neural networks based on multi-valued and universal binary neurons
Multi-valued and universal binary neurons (MVN and UBN) are the neural processing elements with the complex-valued weights and high functionality. It is possible to implement an arbitrary mapping described by partially defined multiplevalued function on the single MVN. An arbitrary mapping described by partially defined or fully defined Boolean function, which can be non-threshold, may be implemented on the single UBN. The quickly converging learning algorithms exist for both types of neurons. Such features of the MVN and UBN may be used for solving the different problems. One of the most successful applications of the MVN and UBN is their usage as basic neurons in the Cellular Neural Networks (CNN). It opens the new effective opportunities in nonlinear image filtering and its applications to noise reduction, edge detection and solving of the super resolution problem. A number of experimental results are presented to illustrate the performance of the proposed algorithms.
Igor N. Aizenberg, Constantine Butakoff
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 2002
Where VLSISP
Authors Igor N. Aizenberg, Constantine Butakoff
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