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1 2008

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Self organizing neural network (SONN) based gray scale object extractor with a multilevel sigmoidal (MUSIG) activation function

Bhattacharyya S., Dutta P., Maulik U.

Foundations of Computing and Decision Sciences

2008

Vol. 33, No. 2

131-165

A single three layer self organizing neural network, characterized by the standard bilevel sigmoidal activation function, is efficient in extraction of binary objects from a noisy image by means of self supervision. A multilevel version of the generalized sigmoidal activation function for mapping multiscale input information into multiple scales of gray, is introduced in this article. The multilevel function is used to induce multiscaling capability in a single three layer self organizing neural network. An application of the proposed multilevel activation function for the extraction of multiscale images, is demonstrated using a synthetic and two real life multiscale images. Experiments have been conducted with different combinations of parameters of the function. The standard correlation factors between the extracted and the original images indicate the efficiency of the proposed multilevel activation function.