The lateral inhibition as conditional entropy enhancer

Authors : Sefa Yıldırım, Zulfiye Arikan, Serhan Ozdemir

Pages : 24-30

Doi:10.26701/ems.320033

View : 23 | Download : 11

Publication Date : 2017-03-20

Article Type : Research Paper

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  insert ignore into journalissuearticles values(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