A note on sampling and parameter estimation in linear stochastic systems

Duncan, Tyrone E.; Mandl, P.; Pasik-Duncan, Bozenna

dc.contributor.author	Duncan, Tyrone E.
dc.contributor.author	Mandl, P.
dc.contributor.author	Pasik-Duncan, Bozenna
dc.date.accessioned	2007-04-06T14:31:24Z
dc.date.available	2007-04-06T14:31:24Z
dc.date.issued	1999-11
dc.identifier.citation	Duncan, TE; Mandl, P; Pasik-Duncan, B. A note on sampling and parameter estimation in linear stochastic systems. IEEE TRANSACTIONS ON AUTOMATIC CONTROL. November 1999. 44(11) : 2120-2125
dc.identifier.other	Digital Object Identifier 10.1109/9.802928
dc.identifier.uri	http://hdl.handle.net/1808/1294
dc.description	©1999 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
dc.description.abstract	Numerical differentiation formulas that yield consistent least squares parameter estimates from sampled observations of linear, time invariant higher order systems have been introduced previously by Duncan et al. The formulas given by Duncan ct ai. have the same limiting system of equations as in the continuous time case. The formula presented in this note can be characterized as preserving asymptotically a partial integration rule. It leads to limiting equations for the parameter estimates that are different from the continuous case, but they again imply consistency. The numerical differentiation formulas given here can be used for an arbitrary linear system, which is not the ease in the previous paper by Duncan et al.
dc.language.iso	en_US
dc.publisher	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
dc.subject	Estimation
dc.subject	Linear stochastic systems
dc.subject	Numerical differentiation for stochastic systems
dc.subject	Sampling
dc.title	A note on sampling and parameter estimation in linear stochastic systems
dc.type	Article
dc.rights.accessrights	openAccess

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