Search results for "NETWORKS"
showing 10 items of 3260 documents
Digital information receiver based on stochastic resonance
2003
International audience; An electronic receiver based on stochastic resonance is presented to rescue subthreshold modulated digital data. In real experiment, it is shown that a complete data restoration is achieved for both uniform and Gaussian white noise.
Learning with belief levels
2008
AbstractWe study learning of predicate logics formulas from “elementary facts,” i.e. from the values of the predicates in the given model. Several models of learning are considered, but most of our attention is paid to learning with belief levels. We propose an axiom system which describes what we consider to be a human scientist's natural behavior when trying to explore these elementary facts. It is proved that no such system can be complete. However we believe that our axiom system is “practically” complete. Theorems presented in the paper in some sense confirm our hypothesis.
Preface
2019
The Enrico Fermi Schools are a highly prestigious series of summer schools of the Italian Physical Society with a tradition of more than 60 years and with many Nobel laureates as lecturers (https://www.sif.it/attivita/scuola_fermi/). The International Schools devote special care in planning the program and produces proceedings of the school that have become classics. Recently an increasing number of interdisciplinary topics have been selected and our school fits into this trend. Our school will consider complex systems of social and economic origin by teaching and discussing concepts and topics of computational social science and econophysics. These are fields, where physicists, computer sc…
Incremental Generalized Discriminative Common Vectors for Image Classification.
2015
Subspace-based methods have become popular due to their ability to appropriately represent complex data in such a way that both dimensionality is reduced and discriminativeness is enhanced. Several recent works have concentrated on the discriminative common vector (DCV) method and other closely related algorithms also based on the concept of null space. In this paper, we present a generalized incremental formulation of the DCV methods, which allows the update of a given model by considering the addition of new examples even from unseen classes. Having efficient incremental formulations of well-behaved batch algorithms allows us to conveniently adapt previously trained classifiers without th…
Day-ahead forecasting for photovoltaic power using artificial neural networks ensembles
2016
Solar photovoltaic plants power output forecasting using machine learning techniques can be of a great advantage to energy producers when they are implemented with day-ahead energy market data. In this work a model was developed using a supervised learning algorithm of multilayer perceptron feedforward artificial neural network to predict the next twenty-four hours (day-ahead) power of a solar facility using fetched weather forecast of the following day. Each set of tested network configuration was trained by the historical power output of the plant as a target. For each configuration, one hundred networks ensembles was averaged to give the ability to generalize a better forecast. The train…
Achieving energy efficiency in data centers with a performance-guaranteed power aware routing
2017
Nowadays, data centers are designed to offer the highest performance in case of high traffic load and peak utilisation of the network. However, in a realistic data center environment, the peak capacity of the network is rarely reached and the average utilisation of devices varies between 5% and 25% which results into a huge loss of energy since most of the time links and servers are idle or under-utilized. The high impact of this wasted power on environmental effects, energy needs and electricity costs raised the concerns to seek for an efficient solution to make data centers more power effective while keeping the desired quality of service. In this paper, we propose a power-aware routing a…
Fully Automatic Trunk Packing with Free Placements
2010
We present a new algorithm to compute the volume of a trunk according to the SAE J1100 standard. Our new algorithm uses state-of-the-art methods from computational geometry and from combinatorial optimization. It finds better solutions than previous approaches for small trunks.
Special issue on the occasion of the International Workshop on Complex Networks and their Applications
2014
Ein Verfahren zur Behandlung von Ausgleichsaufgaben mit Intervallkoeffizienten
1976
Es wird ein Verfahren beschrieben, das die Berechnung einer Intervalleinschliesung der Losungsmenge einer linearen Ausgleichsaufgabe mit Intervallkoeffizienten erlaubt. Es stellt eine Ubertragung des Bjorckschen Algorithmus der iterativen Verbesserung einer Naherungslosung zu einer linearen Ausgleichsaufgabe [5] auf ein bekanntes Verfahren zur Behandlung von Intervallgleichungssystemen dar.
A-stabile Kollokationsverfahren mit mehrfachen Knoten
1982
Die Kollokationsmethoden, die vom Autor in [3] untersucht werden, liefern Spline-Approximationen fur die Losungen von Anfangswertproblemen bei gewohnlichen Differentialgleichungen. Einige allgemeine Resultate uber A-Stabilitat von Wanner, Hairer und Norsett [6] werden fur diese Methoden in dem Fall formuliert, wo sie mit gewissen impliziten Runge-Kutta-Methoden aquivalent sind. Hierbei wird die Abhangigkeit der A-Stabilitat von den Knoten und ihren Vielfachheiten offensichtlich.