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In this talk, we first review some related progresses on one dimensional shallow water models. Then we introduce the derivation of a new nonlocal shallow water model from the 3D Euler system with free...
We develop the Double Principal Component Analysis (DPCA) based on a dual factor structure for high-frequency intraday returns contaminated by microstructure noise. The dual factor structure allows a ...
This talk considers the distributed estimation problem of a linear stochastic system described by an autoregressive model with exogenous inputs when both the system orders and parameters are unknown. ...
The contribution is part of an interdisciplinary research that aims to address the problems of knowledge, interpretation and documentation of vulnerable structures such as the brick Renaissance domes ...
Relatively total variation (RTV) algorithm, which can effectively decompose structure information and texture in image, is employed in extracting main structures of the image. However, applying the RT...
The aim of the present research is to develop an instrument able to adequately support the conservation process by means of a twofold approach, based on both BIM environment and ontology formalisation...
In this paper, we consider a spatial-autoregressive model with autoregressive disturbances, where we allow for endogenous regressors in addition to a spatial lag of the dependent variable. We sugges...
We adapt an information theory analysis of interacting cognitive biological and social modules to the problem of the global neuronal workspace, the new standard neuroscience paradigm for consciousness...
New techniques are presented for the model reduction of linear time-varying and linear periodically-varying systems, including the formulation and proof of guaranteed upper bounds for the error. The c...
This paper focuses on methods of constructing of reduced-order models of mechanical systems which preserve the Lagrangian structure of the original system. These methods may be used in combination wit...
Error-bounds are developed for balanced truncation of linear time-varying systems, leading to an extension of the `twice the sum of the tail' formulae, well-known in the time-invariant case. The appro...
A general approach to the dimensional reduction of non-linear finite element models of solid dynamics is presented. For the Newmark implicit time-discretization, the computationally most expensive pha...
In this paper we introduce a new method of model reduction for nonlinear control systems. Our approach is to construct an approximately balanced realization. The method requires only standard matrix c...
In this paper, we apply a principal-orthogonal decomposition based method to the model reduction of a hybrid, nonlinear model of a power network. The results demonstrate that the sequence of fault eve...
We propose a computational approach to systematically find decentralized H-infinity suboptimal controllers for general unstructured models. Exploiting the quadratically invariant model projection and ...

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