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Noise Filtering in Cellular Neural Networks

  • Mikhail S. TarkovEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11554)

Abstract

A cellular neural network (CNN) with a bipolar stepwise activation function is considered. A comparative analysis of CNN learning algorithms on a given set of binary reference images for various degrees of noise (inversion of randomly selected pixels) and various cell neighborhood sizes is performed. For CNN training a local projection method, which provides much higher noisy images quality filtering than the classical local perceptron learning algorithm, is proposed.

Keywords

Cellular neural network Noise filtering Perceptron training algorithm Local projection method Noisy images Cell neighborhood 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Rzhanov Institute of Semiconductor Physics SB RASNovosibirskRussia

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