The cost of complexity in identification of FIR systems

• In this paper we investigate the minimum amount of input power required to estimate a given linear system with a prescribed degree of accuracy, as a function of the model complexity. This quantity is defined to be the "cost of complexity". The degree of accuracy considered is the maximum variance of the discrete-time transfer function estimator over a frequency range [-ωB, ωB]. It is commonly believed that the cost increases as the model complexity increases. The objective of this paper is to quantify this dependence. In particular, we establish several properties of the cost of complexity. We find, for example, a lower bound for the cost asymptotic in the model order. For simplicity, we consider only systems described by FIR models and assume that there is no undermodelling.

Ämnesord

TEKNIK OCH TEKNOLOGIER  -- Elektroteknik och elektronik -- Reglerteknik (hsv//swe)

ENGINEERING AND TECHNOLOGY  -- Electrical Engineering, Electronic Engineering, Information Engineering -- Control Engineering (hsv//eng)

Nyckelord

Identification for control

Input and excitation design

Cost-increases

Degree of accuracy

Discrete-time

FIR model

FIR systems

Frequency ranges

Input power

Lower bounds

Maximum variance

Model complexity

Model order

Control theory

Costs

FIR filters

Frequency estimation

Linear systems

Identification (control systems)

SRA - ICT

SRA - Informations- och kommunikationsteknik

Publikations- och innehållstyp

ref (ämneskategori)

kon (ämneskategori)