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Grant Award View - GA2267

Modeling stochastic systems in Riemannian manifolds

Contact Details

ARC NCGP General Enquiries

Phone:
02 6281 6600

Email Address:

GA ID:
GA2267
Agency:
Australian Research Council
Approval Date:
10-Nov-2017
Publish Date:
20-Feb-2018
Category:
Science, Technology, Engineering and Mathematics (STEM) Research
Grant Term:
1-Jan-2018 to 31-Dec-2020
Value (AUD):
$362,716.00 (GST inclusive where applicable)

Ad hoc/One-off:
No
Aggregate Grant Award:
No

PBS Program Name:
ARC 17/18 Discovery
Grant Program:
Discovery Projects
Grant Activity:
Modeling stochastic systems in Riemannian manifolds
Purpose:
This project aims to develop new statistical signal processing and control engineering algorithms and tools that will enable tracking of objects remotely on land and in space. A growing number of applications require the study of random processes in Riemannian manifolds, that is processes that evolve subject to a geometric constraint. This project aims to provide methods for the numerical simulation of such processes, methods of online and offline system identification from data on such processes and asymptotic performance analysis; and algorithms for process state estimation that obeys the geometry. The outcomes will advance and benefit spatio-temporal data analysis in areas such as transport, health and video-security.

Internal Reference ID:
DP18 Round 1
Selection Process:
Targeted or Restricted Competitive

Confidentiality - Contract:
No
Confidentiality - Outputs:
No

Grant Recipient Details

Recipient Name:
The University of New South Wales
Recipient ABN:
57 195 873 179

Grant Recipient Location

Suburb:
KENSINGTON
Town/City:
KENSINGTON
Postcode:
2033
State/Territory:
NSW
Country:
AUSTRALIA

Grant Delivery Location

State/Territory:
NSW
Postcode:
2033
Country:
AUSTRALIA

Contact Details

ARC NCGP General Enquiries

Phone:
02 6281 6600

Email Address: