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ce 331: 1433-1436. 35. JimenexJl• NUM./Ironer R. Campbell OW, Turk•Nlaclend It, Chen IA )2013) I:omprrhent
logy I www.ploscompbiol.org 3 September 2014 I Volume 10 I Issue 9 I el 0038113 EFTA00611790 The Time Scale of Evolutionary Innovation Table 1. Numerical data for discovery time in flat fitness landscapes. r.i 3 1 2 3 r= - 4 L=103 1.021011 136.107 183 L=101 3.8910I” 1.28.104' 2666 Numerical
nce 331: 1433 1436. 35 Jimenezjl. Xulti-Bonet R. Campbell GW, Ttuk•Malend K. Chen IA (2013) Comprehensive
iology I www.ploscompbiol.org 3 September 2014 I Volume 10 I Issue 9 I e1003818 EFTA00611783 The Time Scale of Evolutionary Innovation Table 1. Numerical data for discovery time in flat fitness landscapes. r.I L=102 1.021018 7.36107 183 L=10' 5.89 1.28.100 2666 Numerical data for the discover
A97:227-230. Grassberger, P, Procaccia, |. (1983) Measuring the strangeness of strange attractors. Physica 9D:189-208 Gregson, R.A.,Britton, L.A., Campbell, E.A., Gates, G.R. (1990) Comparisons of the nonlinear dynamics of electroencephalograms under various task loading conditions: a preliminary report
nt and attractor dimension curves of EEG in sleep. Comput Biol Med 26:419-428 Press, W.H., Flannery, B.P., Teukolsky, S.A., Vetterling, W.T. (1991) Numerical Recipies; The Art of Scientific Computing. Cambridge University Press, Cambridge. Pritchard, W.S. (1992) The brain in fractal time: 1/f-like power s
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