Results 61 to 70 of about 586,238 (144)

TSALLIS ENTROPY BASED SEIZURE DETECTION [PDF]

open access: yes, 2021
This paper presents EEG signal analysis using Tsallis entropy and then it will make available for comparison with any another method along with KNN classification. Electroencephalogram (EEG) remains the most immediate, easy and rich source of information
MR.S.S.PAWAR   +1 more
core   +1 more source

Weak chaos from Tsallis entropy

open access: yes, 2012
We present a geometric, model-independent, argument that aims to explain why the Tsallis entropy describes systems exhibiting “weak chaos”, namely systems whose underlying dynamics has vanishing largest Lyapunov exponent.
Nikos Kalogeropoulos
core   +1 more source

Quantum conditional relative entropy and quasi-factorization of the relative entropy [PDF]

open access: yes, 2018
The existence of a positive log-Sobolev constant implies a bound on the mixing time of a quantum dissipative evolution under the Markov approximation.
Pérez García, David   +3 more
core   +1 more source

Tsallis Entropy from Maximization of Entropy and the Condition of Stability

open access: yes
In  a previous note (1), we argued that in the Maxwell-Boltzmann (Shannon) case, one may either maximize Shannon’s entropy:  - Sum over i p(ei) ln(p(ei)) subject to the two a priori constraints: Sum over i p(ei)=1 and Sum over i ei p(ei) = Etotal or use reaction balance: e1+e2=e3+e4 and p(e1)p(e2)=p(e3)p(e4).
openaire   +2 more sources

Tsallis Entropy from Maximization of Entropy and the Condition of Stability Part 2

open access: yes
 In Part I, we argued that F(p(ei/T)) = -ei/T, where p(ei/T) is an unnormalized probability. We suggested that one may find Tsallis entropy from p(ei) power q dF/dp(ei) =1  ((1)), where F= lnq(p(ei)) and Tsallis entropy is:  Sum over i   p(ei) power q lnq(p(ei)). We argued that this was due to stability considerations.
openaire   +2 more sources

Tsallis Entropy from Maximization of Entropy and the Condition of Stability Part 3

open access: yes
 In the note, we argue that statistical mechanics, at least with respect to Boltzmann/Shannon entropy and Tsallis entropy, may be formulated strictly through information related to -ei/T considerations. In fact, as argued in Part 2, there is no need for any notion of maximization of entropy subject to constraints or even reaction balance in the case of
openaire   +1 more source

Tsallis Entropy, Escort Probability and the Incomplete Information Theory

open access: yes, 2010
Non-extensive statistical mechanics appears as a powerful way to describe complex systems. Tsallis entropy, the main core of this theory has been remained as an unproven assumption. Many people have tried to derive the Tsallis entropy axiomatically. Here
Parvin Sadeghi   +3 more
core   +1 more source

Is the Tsallis entropy stable?

open access: yes, 2009
The question of whether the Tsallis entropy is Lesche-stable is revisited. It is argued that when physical averages are computed with the escort probabilities, the correct application of the concept of Lesche-stability requires use of the escort ...
J. P. Boon   +5 more
core   +1 more source

Non-parametric Estimation of Tsallis Entropy and Residual Tsallis Entropy Under $$\rho $$-Mixing Dependent Data

open access: yes
In 1988, Tsallis introduced a non-logarithmic generalization of Shannon entropy, namely Tsallis entropy, and it is non-extensive. In the present work, we propose non-parametric kernel type estimators for the Tsallis entropy and the residual Tsallis ...
Maya, R.   +4 more
core   +1 more source

Volatility models with innovations from new maximum entropy densities at work [PDF]

open access: yes
Generalized autoregressive conditional heteroskedasticity (GARCH) processes have become very popular as models for financial return data because they are able to capture volatility clustering as well as leptokurtic unconditional distributions which ...
Herrmann, Klaus   +2 more
core  

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