Fractals and Chaos Simplified for the Life Sciences

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Page 267
126
phase space 122, 126, 136
vs. deterministic 116-119, 122, 126, 136, 142, 148, 152, 188, 192
ion channels 200-205
problems with the analysis 206-217, 222
surrogate data sets 220-221
vectors in phase space 218, 219
Rapp 199
Rauseo 231
reaction rates 40, 68, 180-185
references suggested
chaos 240, 241
fractals 110, 111
other methods 248, 249
Reid 67
relative dispersion 88, 89, 98
resonance 202
retina 14, 15, 62, 70
Richardson 33
rocks 82
root mean square (RMS) 82
Roy 229
S
sample mean 74, 78, 80, 84
scaling, fractals (see fractals, scaling)
Scanlan 203
Schaffer 195
Scholz 83
Seeley 97
Selector 17
self-organization 186
self-organizing critical systems 248, 249
self-similarity dimension (see dimension, self-similarity)
self-similarity, fractals (see fractals, self-similarity)
sensitivity to initial conditions (see chaos, sensitivity to initial conditions)
sensory phase transition 186
shadowing theorem 170, 171
Sheriff 15
Shrier 145, 147
significant digits 162
Skarda 199
Smith 15, 211
Sobotka 197
Spano 231
St. Petersburg Game 78, 79, 94, 95
stable 234
standard deviation 98
Stanley 15, 81, 99
stationary 104
statistical properties (see fractals, statistical properties)
statistical self-similarity 12
statistical tests 102
Stewart 93
strange attractor 132, 158, 166-169
substances in the blood 40
sugar 180-185
summaries
chaos (Part 1, Chapter 7) 237-241
fractals (Part 1, Chapter 6) 107-111
other methods 248, 249
surrogate data set 220, 221
synergetics 186
T
T-lymphocytes 16, 17, 100
Tacoma Narrows Bridge 202, 203
Takens' theorem 138, 214, 215
teeth 68
Teich 85, 87, 99, 141
Theiler 221
theorem
central limit 86
embedding 122, 130, 138, 142
shadowing 170, 171
Takens' 138, 214, 215
thermodynamic equilibrium 204

 
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