The CNN solution to the shortest-path-finder problem

Algorithms to find the shortest path within the CNN context are a classical problem nowadays. An important attempt to solve this problem by parallel computing using the properties of autowaves was analyzed. Nevertheless, these solutions were unpractical as they required each cell of the system to re...

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Bibliographic Details
Published in2008 11th International Workshop on Cellular Neural Networks and Their Applications pp. 248 - 251
Main Authors Muuzuri, A.P., Vazquez-Otero, A.
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.07.2008
Subjects
Cellular neural networks
Color
Evolution (biology)
Filtering algorithms
Image processing
Joining processes
Robustness
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ISBN142442089X
9781424420896
ISSN2165-0144
DOI10.1109/CNNA.2008.4588686

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Summary:Algorithms to find the shortest path within the CNN context are a classical problem nowadays. An important attempt to solve this problem by parallel computing using the properties of autowaves was analyzed. Nevertheless, these solutions were unpractical as they required each cell of the system to remember when a wave went through it. In this text, anomalous properties of autowaves are used to solve the shortest-path-finder problem in a very robust, self-content way.
ISBN:142442089X
9781424420896
ISSN:2165-0144
DOI:10.1109/CNNA.2008.4588686