Optimization of multidimensional scalar and block state-space models

Author

Ju, Chwen-Jye

Author_Institution

Sharp Microelectron. Technol. Inc., Camas, WA, USA

fYear

1991

fDate

11-14 Jun 1991

Firstpage

2784

Abstract

Necessary and sufficient conditions of optimizing 2D Roesser´s state-space models by using 1D optimization algorithms are proposed. The 2D optimizing algorithm based upon S.Y. Hwang´s (1977) approach is then given. In addition, the N-D equivalent invariant relation between N-D scalar and block state-space models is investigated. It is shown that under the criterion of minimizing the average output roundoff noise variance with the same dynamic range constraint, the extended block state-space model will be optimized, if the original scalar state-space model is optimized

Keywords

digital filters; filtering and prediction theory; optimisation; random noise; roundoff errors; state-space methods; 1D optimization algorithms; 2D Roesser´s state-space models; IIR filter; N-D equivalent invariant relation; block state-space models; digital filters; dynamic range constraint; multidimensional scalar model; roundoff errors; Constraint optimization; Covariance matrix; Digital filters; Dynamic range; Equations; Matrix decomposition; Microelectronics; Multidimensional systems; Roundoff errors; Sufficient conditions;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 1991., IEEE International Sympoisum on

Print_ISBN

0-7803-0050-5

Type

conf

DOI

10.1109/ISCAS.1991.176122

Filename

176122