Sefa Yıldırım, Zulfiye Arikan, Serhan Ozdemir

The lateral inhibition as conditional entropy enhancer

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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Coskun, A., Sevil, H.E., and Ozdemir, S. (2011). Cost effective localization in distributed sensory networks. Engineering Applications of Artificial Intelligence, vol. 24, no. 2, pp. 232-237. 10.1016/j.engappai.2010.10.006
Hartline, H.K., Wagner, H.G., and Ratliff, F. (1956). Inhibition in the eye of Limulus. The Journal of general physiology, vol. 39, no. 5, pp. 651-673.
Barlow, R.B. (1969). Inhibitory fields in the Limulus lateral eye. The Journal of general physiology, vol. 54, no. 3, pp. 383-396.
Von Békésy, G., (1967) Sensory inhibition (The Herbert Sidney Langfeld memorial lectures,, no. 1965). Princeton, N.J.,: Princeton University Press, pp. x, 265 p.
Brooks, M., "Highly redundant sensing in robotics—analogies from biology: distributed sensing and learning," in Highly Redundant Sensing in Robotic Systems: Springer, 1990, pp. 35-42.
Shannon, C.E. (2001). A mathematical theory of communication. ACM SIGMOBILE Mobile Computing and Communications Review, vol. 5, no. 1, pp. 3-55.
Nyquist, H. (1924). Certain factors affecting telegraph speed. Transactions of the American Institute of Electrical Engineers, vol. 43, pp. 412-422.
Hartley, R.V. (1928). Transmission of information. Bell Labs Technical Journal, vol. 7, no. 3, pp. 535-563.
Coşkun, A. (2006) Contrast enhancement by lateral inhibition in a sensory network, M.Sc., İzmir Institute of Technology.
Haykin, S.S., (2001) Neural networks: a comprehensive foundation. Tsinghua University Press.
Erdogmus, D., Agrawal, R., and Principe, J.C. (2005). A mutual information extension to the matched filter. Signal Processing, vol. 85, no. 5, pp. 927-935. 10.1016/j.sigpro.2004.11.018

Yayın Aralığı: 4
Başlangıç: 2017
Yayıncı: Ahmet Çalık

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