  Symbolic transformation, a coarse-graining process, is a crucial prerequisite
for and has evidential influence to the symbolic time series analysis. We
employ Shannon entropy for a parameter-dependent symbolization, KW
(Kurths-Wessel) symbolic method, to test the effects of controlling parameter
on its symbolic nonlinear complexity detection. Two chaotic models, logistic
and Henon series, and heartbeats of CHF (Congestive Heart Failure) patients,
healthy young and elderly subjects from PhysioNet are applied to test the KW
symbolic entropy. The complexity-loss theory about aging and diseases in heart
rates is validated and reasons that may account for some paradoxes in nonlinear
analysis are discussed. Tests results suggest that due to different structural
or dynamical properties of different nonlinear systems, controlling parameter
of the KW symbolization should be adjusted accordingly to have reliable
symbolic nonlinear analysis.
