Cloud-aided collaborative estimation by ADMM-RLS algorithms for connected diagnostics and prognostics

As the connectivity of consumer devices is rapidly growing and cloud computing technologies are becoming more widespread, cloud-aided algorithms for parameter estimation can be developed to exploit the theoretically unlimited storage memory and computational power of the 'cloud', while relying on information provided by multiple sources. With the ultimate goal of developing monitoring, diagnostic and prognostic strategies, this paper focuses on the design of a Recursive Least-Squares (RLS) based estimator for identification over a multitude of similar devices (such as a mass production) connected to the cloud. The proposed approach, that relies on Node-to-Cloud-to-Node (N2C2N) transmissions, is designed so that: (i) estimates of the unknown parameters are computed locally and (ii) the local estimates are refined on the cloud by exploiting the additional information that the devices have similar characteristics. The proposed approach requires minimal changes to local (pre-existing) RLS estimators

MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described

Generalized averaged Gaussian quadrature and applications

A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal