Effects of correlated variability on information entropies in nonextensive systems

Abstract

We have calculated the Tsallis entropy and Fisher information matrix (entropy) of spatially-correlated nonextensive systems, by using an analytic non-Gaussian distribution obtained by the maximum entropy method. Effects of the correlated variability on the Fisher information matrix are shown to be different from those on the Tsallis entropy. The Fisher information is increased (decreased) by a positive (negative) correlation, whereas the Tsallis entropy is decreased with increasing an absolute magnitude of the correlation independently of its sign. This fact arises from the difference in their characteristics. It implies from the Cramér-Rao inequality that the accuracy of unbiased estimate of fluctuation is improved by the negative correlation. A critical comparison is made between the present study and previous ones employing the Gaussian approximation for the correlated variability due to multiplicative noise.

21 pages, 7 figures: accepted in Phys. Rev. E with minor changes

References in corpus (4)

• A possible deformed algebra and calculus inspired in nonextensive thermostatistics
• A moment approach to non-Gaussian colored noises
• Generalized information-entropy measures and Fisher information
• Stationary and dynamical properties of information entropies in nonextensive systems

Cited by in corpus (3)

• Population rate codes carried by mean, fluctuation and synchrony of neuronal firings
• Synchrony and variability induced by spatially correlated additive and multiplicative noise in the coupled Langevin model
• Dynamics of Information Entropies in Nonextensive Systems