Introduction to Classical Identification

The purpose of this section is to expose the reader to the acknowledged scholarly field of deducing, or inferring, structure and dynamics from measurements, also called classical identification (see [2] and [3] for representative references). This is well known to 

Analysis by linear regression is the fit of given measurements by a straight line. The programs LISREL and SEPATH (see [4]-[7]) provide linear regression with some causal input. The linear or linearized response of a system to a small perturbation depends on the location of the system in the space of its variables. To obtain a linear response in a possibly nonlinear system requires small perturbations, and hence to be useful the errors in the measurements must be small—smaller than the perturbations. The issues of importance here are  

Observability. Perturb one species and see what you can determine, that is, measure, about the other species. 

Controllability. For a given system, can you perturb at a point A in the space of the variables and from there come to another point B  

Reachability. Is the attainment of point B from point A feasible  

---