Information Technology Reference
In-Depth Information
[62] L. Silvestri, L. Fronzoni, P. Grigolini and P. Allegrini, “Event driven power-law relaxation
in weak turbulence,”
Phys. Rev. Lett
.
102
, 014502 (2009).
[63] R. G. Turcott, P. D. Barker and M. C. Teich, “Long-duration correlation in the sequence of
action potentials in an insect visual interneuron,”
J. Statist. Comput. & Simul
.
52
, 253-271
(1995).
[64] M. Turalska, M. Lukovic, B. J. West and P. Grigolini, “Complexity and synchronization,”
Phys. Rev. E
80
, 021110-1 (2009).
[65] D. Vitali and P. Grigolini, “Subdynamics, Fokker-Planck equation, and exponential decay
of relaxation processes,”
Phys. Rev. A
39
, 1486-1499 (1989).
[66] L. M. Ward, “Physics of neural synchronization mediated by stochastic resonance,”
Con-
temp. Phys
.
50
, 563-574 (2009).
[67] A. Weron, M. Magdziarz and K. Weron, “Modeling of subdiffusion in space-time-dependent
force fields beyond the fractional Fokker-Planck equation,”
Phys. Rev. E
77
, 036704 (2008).
[68] B. J. West, E. L. Geneston and P. Grigolini, “Maximizing information exchange between
complex networks,”
Phys. Rep.
468
, 1-99 (2008).
[69] B. J. West and P. Grigolini, “Statistical habituation model and 1/
f
noise,”
Physica A
doi: 10.1016/j.physa.2010.08.033 (2010).
[70] J. C. Willis and G. U. Yule, “Some statistics of evolution and geographical distribution in
plants and animals, and their signature,”
Nature
109
, 177-179 (1922).
[71] G. U. Yule, “A mathematical theory of evolution based on the conclusions of Dr. J. C.
Willis,”
Philos. Trans. R. Soc. London B
213
, 21-87 (1925).
[72] E. Zohary, M. N. Shadlen and W. T. Newsome, “Correlated neuronal discharge rate and its
implications for psychophysical performance,”
Nature
370
, 140 (1994).
[73] R. Zwanzig,
Nonequilibrium Statistical Mechanics
, New York: Oxford University Press
(2001).