東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Optimal sensor placement for paramet...

Green, Kary.

Linked to FindBook

Google Book

Amazon

博客來

Optimal sensor placement for parameter identification.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Optimal sensor placement for parameter identification./
Author:	Green, Kary.
Description:	55 p.
Notes:	Adviser: Matthias Heinkenschloss.
Contained By:	Masters Abstracts International45-04.
Subject:	Engineering, System Science. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1441820

Optimal sensor placement for parameter identification.
Green, Kary.

Optimal sensor placement for parameter identification. - 55 p.

Adviser: Matthias Heinkenschloss.

Thesis (M.A.)--Rice University, 2007.

This thesis surveys methods for determining sensor locations which maximize the achievable accuracy in parameter estimation of differential equations. The approach considers the placement of sensors as an experimental design problem. The optimal sensor locations are found based on the so-called Fisher Information Matrix. After illustration of the general methodology, a particular algorithm is presented which finds optimal weights associated with a given set of potential sensor locations. Numerical results are provided to show that improvements in the accuracy of parameter estimates can be achieved using the ideas reviewed in this thesis.Subjects--Topical Terms:

1018128
Engineering, System Science.

Optimal sensor placement for parameter identification.
LDR:01478nam 2200277 a 45 001 942566
005 20110519
008 110519s2007 eng d
035 $a (UMI)AAI1441820
035 $a AAI1441820
040 $a UMI $c UMI
100 1 $a Green, Kary. $3 1266668
245 1 0 $a Optimal sensor placement for parameter identification.
300 $a 55 p.
500 $a Adviser: Matthias Heinkenschloss.
500 $a Source: Masters Abstracts International, Volume: 45-04, page: 1980.
502 $a Thesis (M.A.)--Rice University, 2007.
520 $a This thesis surveys methods for determining sensor locations which maximize the achievable accuracy in parameter estimation of differential equations. The approach considers the placement of sensors as an experimental design problem. The optimal sensor locations are found based on the so-called Fisher Information Matrix. After illustration of the general methodology, a particular algorithm is presented which finds optimal weights associated with a given set of potential sensor locations. Numerical results are provided to show that improvements in the accuracy of parameter estimates can be achieved using the ideas reviewed in this thesis.
590 $a School code: 0187.
650 4 $a Engineering, System Science. $3 1018128
650 4 $a Mathematics. $3 515831
650 4 $a Statistics. $3 517247
690 $a 0405
690 $a 0463
690 $a 0790
710 2 $a Rice University. $3 960124
773 0 $t Masters Abstracts International $g 45-04.
790 $a 0187
790 1 0 $a Heinkenschloss, Matthias, $e advisor
791 $a M.A.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=1441820