Singular value decomposition in sensitivity minimisation for digital filters

Author

Tavsanoglu, Vedat

Author_Institution

Sch. of Electr., Electron. & Inf. Eng., South Bank Univ., London, UK

fYear

1993

fDate

3-6 May 1993

Firstpage

152

Abstract

The singular value decomposition (SVD) is used in the minimization of a previously given integral sensitivity measure. It is shown that the necessary and sufficient condition for the minimum of this measure is that the integrand, the frequency-dependent measure (FDSM), takes its minimum value with respect to the singular values of the transformation matrix T. This minimum is an attainable lower bound of the FDSM for all values of z for any transfer function. It is shown that this case corresponds to internally balanced realization (IBR) and any realization within an orthogonal transformation of the IBR

Keywords

digital filters; filtering theory; matrix algebra; minimisation; sensitivity analysis; singular value decomposition; transfer functions; SVD; digital filters; frequency-dependent measure; integral sensitivity measure; internally balanced realization; orthogonal transformation; sensitivity minimisation; singular value decomposition; transfer function; transformation matrix; Digital filters; Electric variables measurement; Frequency measurement; Integral equations; Length measurement; Matrix decomposition; Singular value decomposition; Sufficient conditions; Transfer functions; Upper bound;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1993., ISCAS '93, 1993 IEEE International Symposium on

Conference_Location

Chicago, IL

Print_ISBN

0-7803-1281-3

Type

conf

DOI

10.1109/ISCAS.1993.393680

Filename

393680