an algorithmic complexity interpretation of lins third law of information theory林一个算法复杂度的解释信息理论的第三定律.pdfVIP

an algorithmic complexity interpretation of lins third law of information theory林一个算法复杂度的解释信息理论的第三定律.pdf

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an algorithmic complexity interpretation of lins third law of information theory林一个算法复杂度的解释信息理论的第三定律

Entropy 2008, 10, 6-14 entropy ISSN 1099-4300 c 2008 by MDPI /entropy/ Full Paper An Algorithmic Complexity Interpretation of Lin’s Third Law of Information Theory Joel Ratsaby Electrical and Electronic Engineering Department, Ariel University Center of Samaria, Ariel 40700, Israel; E-mail: ratsaby@ariel.ac.il; http://www.ariel.ac.il/ee/pf/ratsaby/ Received: 28 February 2008; in revised form: 16 March 2008 / Accepted: 19 March 2008 / Published: 20 March 2008 Abstract: Instead of static entropy we assert that the Kolmogorov complexity of a static structure such as a solid is the proper measure of disorder (or chaoticity). A static struc- ture in a surrounding perfectly-random universe acts as an interfering entity which introduces local disruption in randomness. This is modeled by a selection rule which selects a subse- quence of the random input sequence that hits the structure. Through the inequality that relates stochasticity and chaoticity of random binary sequences we maintain that Lin’s notion of sta- bility corresponds to the stability of the frequency of s in the selected subsequence. This explains why more complex static structures are less stable. Lin’s third law is represented as the inevitable change that static structure undergo towards conforming to the universe’s perfect randomness. Keywords: Entropy, Randomness, Information theory, Algorithmic complexity, Binary se- quences 1. Introduction Lin [12–14] intr

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