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Minimizing the effects of parameter deviations on cellular neural networks

โœ Scribed by Tetzlaff, R.; Kunz, R.; Wolf, D.

Publisher
John Wiley and Sons
Year
1999
Tongue
English
Weight
299 KB
Volume
27
Category
Article
ISSN
0098-9886

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โœฆ Synopsis

The sensitivity of cellular neural networks (CNN) against random parameter deviations is discussed in detail. For di erent CNN with erroneous parameters the probability is estimated that all cell outputs converge to the same stable รฟxpoint of the corresponding error free CNN. These results are compared with approximations based on a statistical independence assumption. The in uence of deviated parameters is demonstrated for di erent image processing templates. We propose a new parameter learning method for minimizing the e ect of template and bias deviations. In all treated cases a signiรฟcant improvement can be observed by using this method.

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