Dülek, BerkanGezici, Sinan2019-07-022019-07-022012-06http://hdl.handle.net/11693/52094Date of Conference: 17-20 June 2012The well-known problem of estimating an unknown deterministic parameter vector over a linear system subject to additive Gaussian noise is studied from the perspective of minimizing total sensor measurement cost under a constraint on the log volume of the estimation error confidence ellipsoid. A convex optimization problem is formulated for the general case, and a closed form solution is provided when the system matrix is invertible. Furthermore, effects of system matrix uncertainty are discussed by employing a specific but nevertheless practical uncertainty model. Numerical examples are presented to discuss the theoretical results in detail.EnglishWireless sensor networksParameter estimationGaussian noiseMeasurement costConference Paper10.1109/SPAWC.2012.6292923