In the context of signal-based modeling, which of the following best describes the 'black-box' approach to system identification?
Question 2
Consider a physiological system whose response to an input $ u(t) $ is described by the convolution integral: $ y(t) = \int_{-\infty}^{\infty} h(\tau) u(t-\tau) d\tau $. What does $ h(t) $ represent in this context?
Question 3
When performing parameter estimation for a non-linear physiological model, which of the following optimization algorithms is generally preferred due to its ability to handle complex, non-convex error surfaces?
Question 4
Which of the following factors is most critical in determining the appropriate model order for a physiological system during system identification?
Question 5
In the context of parameter estimation, what is the 'Cramér-Rao Lower Bound' primarily used for?
