Learn More
— Recovering or estimating the initial state of a high-dimensional system can require a potentially large number of measurements. In this paper, we explain how this burden can be significantly reduced for certain linear systems when randomized measurement operators are employed. Our work builds upon recent results from the field of Compressive Sensing (CS),(More)
ÐA method is developed to analyze the accuracy of the relative head-to-object position and orientation (pose) in augmented reality systems with head-mounted displays. From probabilistic estimates of the errors in optical tracking sensors, the uncertainty in head-to-object pose can be computed in the form of a covariance matrix. The positional uncertainty(More)
In augmented reality (AR) systems using head-mounted displays (HMD's), it is important to accurately sense the position and orientation (pose) of the user's head with respect to the world, in order that graphical overlays are drawn correctly aligned with real world objects. It is desired to maintain registration dynamically (while the person is moving their(More)
— The thermal storage potential of Thermostatically Controlled Loads (TCLs) is a tremendous flexible resource for providing various ancillary services to the grid. In this work, we study aggregate modeling, characterization, and control of TCLs for frequency regulation service provision. We propose a generalized battery model for aggregating flexibility of(More)
— In this paper, we derive concentration of measure inequalities for compressive Toeplitz matrices (having fewer rows than columns) with entries drawn from an independent and identically distributed (i.i.d.) Gaussian random sequence. These inequalities show that the norm of a vector mapped by a Toeplitz matrix to a lower dimensional space concentrates(More)