• Title/Summary/Keyword: Tsallis-Entropy

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BIVARIATE DYNAMIC CUMULATIVE RESIDUAL TSALLIS ENTROPY

  • SATI, MADAN MOHAN;SINGH, HARINDER
    • Journal of applied mathematics & informatics
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    • v.35 no.1_2
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    • pp.45-58
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    • 2017
  • Recently, Sati and Gupta (2015) proposed two measures of uncertainty based on non-extensive entropy, called the dynamic cumulative residual Tsallis entropy (DCRTE) and the empirical cumulative Tsallis entropy. In the present paper, we extend the definition of DCRTE into the bivariate setup and study its properties in the context of reliability theory. We also define a new class of life distributions based on bivariate DCRTE.

Information Theoretic Learning with Maximizing Tsallis Entropy

  • Aruga, Nobuhide;Tanaka, Masaru
    • Proceedings of the IEEK Conference
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    • 2002.07b
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    • pp.810-813
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    • 2002
  • We present the information theoretic learning based on the Tsallis entropy maximization principle for various q. The Tsallis entropy is one of the generalized entropies and is a canonical entropy in the sense of physics. Further, we consider the dependency of the learning on the parameter $\sigma$, which is a standard deviation of an assumed a priori distribution of samples such as Parzen window.

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A Study on Detecting Selfish Nodes in Wireless LAN using Tsallis-Entropy Analysis (뜨살리스-엔트로피 분석을 통한 무선 랜의 이기적인 노드 탐지 기법)

  • Ryu, Byoung-Hyun;Seok, Seung-Joon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.22 no.1
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    • pp.12-21
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    • 2012
  • IEEE 802.11 MAC protocol standard, DCF(CSMA/CA), is originally designed to ensure the fair channel access between mobile nodes sharing the local wireless channel. It has been, however, revealed that some misbehavior nodes transmit more data than other nodes through artificial means in hot spot area spreaded rapidly. The misbehavior nodes may modify the internal process of their MAC protocol or interrupt the MAC procedure of normal nodes to achieve more data transmission. This problem has been referred to as a selfish node problem and almost literatures has proposed methods of analyzing the MAC procedures of all mobile nodes to detect the selfish nodes. However, these kinds of protocol analysis methods is not effective at detecting all kinds of selfish nodes enough. This paper address this problem of detecting selfish node using Tsallis-Entropy which is a kind of statistical method. Tsallis-Entropy is a criteria which can show how much is the density or deviation of a probability distribution. The proposed algorithm which operates at a AP node of wireless LAN extracts the probability distribution of data interval time for each node, then compares the one with a threshold value to detect the selfish nodes. To evaluate the performance of proposed algorithm, simulation experiments are performed in various wireless LAN environments (congestion level, how selfish node behaviors, threshold level) using ns2. The simulation results show that the proposed algorithm achieves higher successful detection rate.