25th IEEE Conference on Decision and Control, Date: 1986/12/01 - 1986/12/01, Location: Athens, Greece
Proc. of the 25th IEEE Conference on Decision and Control
Author:
Keywords:
SISTA
Abstract:
Some insight is provided in the analysis of the basic modeling problem in the simplest case, i. e. , the identification of linear relations from noisy data. The central idea is the nonuniqueness principle, which states that the solution of a noisy identification problem is intrinsically nonunique. Any uncertainty in the data implies that no particular model can be identified with certainty. In a situation of uncertainty (noise), it is unnatural to have mathematical formulations that lead to unique results. It is demonstrated how classical treatments of the problem have led to a unique solution because additional unverifiable a priori assumptions were imposed that forced uniqueness.