We propose a method for solving continuous-state and action stochastic dynamic programs that is a hybrid between the continuous space projection methods introduced by Judd and the discrete space methods introduced by Bellman. Our hybrid approach yields a smooth representation of the value function while preserving the computational simplicity of discrete dynamic programming. The method is espec...

Non-dictatorial preference domains allow the design of unanimous social choice functions (henceforth, rules) that are non-dictatorial and strategy-proof. On a class called unidimensional domains, we show unique seconds property (introduced by Aswal et al., 2003) characterizes all domains. Subsequently, provide an exhaustive classification non-dictatorial, based on simple two-voter rules invaria...

Data Assimilation (DA) involves the combination of observational data with the underlying dynamical principles governing the system under observation. In this work we combine the advantages of the two prominent DA systems, the 4D-Var and the ensemble methods. The hybrid method described in this paper consists of identifying the subspace spanned by the major 4D-Var error reduction directions. Th...

The Explicitly Restarted Arnoldi Method (ERAM) allows to find a few eigenpairs of a large sparse matrix. The Multiple Explicitly Restarted Arnoldi Method (MERAM) is a technique based upon a multiple projection of ERAM and accelerates its convergence [3]. The MERAM allows to update the restarting vector of an ERAM by taking the interesting eigen-information obtained by the other ones into accoun...

This investigation explores a comparative study of both the linear and kernel implementations of three of the most popular Appearance-based Face Recognition projection classes. These are Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Independent Component Analysis (ICA). The experimental procedure provides a platform of equal working conditions and examines algorithm...

This paper focuses on the adaptation of Automatic Speech Recognition systems using Hybrid models combining Artificial Neural Networks with Hidden Markov Models. A classical adaptation technique consists in adding a linear transformation network that acts as a pre-processor to the main network. We investigated the application of linear transformations not only to the input features, but also to ...

Up to now, several Artificial Intelligence (AI) techniques and paradigms have been successfully applied to the field of Intrusion Detection in Computer Networks. Most of them were proposed to work in isolation. On the contrary, the new approach of hybrid artificial intelligent systems, which is based on the combination of AI techniques and paradigms, is probing to successfully address complex p...

An approach to estimation for a class of hybrid discrete-time linear systems using Luenberger observers is presented. The proposed Luenberger observer for such a kind of systems relies on the switching among different gains. Convergence conditions have been found to ensure the stability of the error dynamics and the related gains may be selected by solving a set of linear matrix inequalities (L...

We study the problem of greedy, single path data propagation in wireless sensor networks, aiming mainly to minimize the energy dissipation. In particular, we first mathematically analyze and experimentally evaluate the energy efficiency and latency of three characteristic protocols, each one selecting the next hop node with respect to a different criterion (minimum projection, minimum angle and...

Because of the different characteristics of Arabic language and Romance and Anglo Saxon languages, recognition of documents written in hybrid of these languages requires that the language of the text to be identified priori to the recognition phase. In this paper, three efficient techniques that can be used to discriminate between text written in Arabic script and text written in English script...