@conference {
	title = {Optimal Stationary Self-Triggered Sampling for Estimation},
	author = {Soleymani, Touraj., Hirche, Sandra., Baras, John S.},
	year = {2016},
	month = {12/2016},
	abstract = {In this paper, we study optimal stationary sampling~for transmission of measurements of a stochastic process~from a source encoder to a source decoder through a costly communication~channel. We measure information transferred over~a time interval by the change in the decoder{\textquoteright}s entropy regarding~the state of the process given the transmitted measurements.~In our setting, the encoder employs a sampler to control the~information flow in the channel. The problem is casted as a~discounted infinite horizon optimization problem that takes into~account the transferred information and the paid price. We~derive the optimal stationary sampling policy, and propose two~computational methods with convergence guarantees by using~techniques from approximate dynamic programing. In addition,~we introduce two triggering mechanisms based on the value of~information and on the covariance threshold that can generate~the optimal policy. Finally, we present some numerical and~simulation results.},
	address = {Las Vegas, Nevada},
	booktitle = {55th IEEE Conference on Decision and Control },
	pages = {pp. 3084-3089}
}
