The lateral inhibition as conditional entropy enhancer
Journal Title: European Mechanical Science - Year 2017, Vol 1, Issue 1
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.
Authors and Affiliations
Sefa Yildirim, Zulfiye Arikan, Serhan Ozdemir
Keywords
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