The lateral inhibition as conditional entropy enhancer

Year 2017, Volume: 1 Issue: 1, 24 - 30, 20.03.2017

Sefa Yıldırım Zulfiye Arikan Serhan Ozdemir

https://doi.org/10.26701/ems.320033

Abstract

Three kinds of redundant sensing have appeared to be utilized by the majority of living beings. Of these, the most remarkable feature of distributed sensor networks is the lateral inhibition (LI),  where  sensors  output  in  proportion  to  its  own  excitation  and  each  sensor  negatively influences its nearest neighbors. This brings about local effects such as contrast enhancement, two-point discrimination, and funneling. In information theory, entropy is a measure of the uncertainty related to a random variable. Shannon entropy, quantifies the anticipated value of the information included in a message, usually in units such as bits. The purpose of this study is to analyze lateral inhibition mechanism in the light of the Shannon entropy.  This  biological  mechanism  can  be  adapted  to  any  artificial  system  such  as  sensory networks. With the aim of adapting this biological mechanism to the sensory networks it is desired to create an information filter with the benefits of information filter feature of lateral inhibition mechanism. The information has to be quantified in order to filter. In this point, the Shannon entropy concept is intended to be used. 

Keywords

Lateral inhibition, mutual information, Shannon entropy

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