Fig. 6.

a A cascade model for the baroreflex neural arc, which consists of a dynamic linear subsystem and a static nonlinear subsystem. The dynamic linear subsystem represents the neural arc transfer function. The static nonlinear subsystem represents the sigmoidal nonlinearity for the neural arc. b Estimation results of the system dynamic characteristics using a Gaussian white noise (GWN) input with a standard deviation (SD) of 10 mmHg. c Estimation results of the system dynamic characteristics using a GWN input with an SD of 20 mmHg. d Estimation results of the system dynamic characteristics using a binary white noise (BIN) input with an amplitude of 10 mmHg. In panels b through d, the thin smooth curve indicates the transfer function of the given dynamic linear subsystem. The solid bold curve, dotted thin curve, and dashed thin curve represent the estimation results obtained by the input signals with mean input pressures of 120, 90, and 150 mmHg, respectively (see text for explanation)