Search results for "parametri"
showing 10 items of 1144 documents
Imbalance Effects in the Lucas Model: An Analytical Exploration
2004
In this note, we use a technique analogous to Xie's method (1994) to solve analytically the Lucas model with externality in a specific parametric case. In particular, we characterize the shape of imbalance effects in this model. Our results are entirely consistent with the findings of the related computational literature. Moreover, our analytical investigation tends to show that these findings are robust to the presence of the Lucas externality as long as a unique equilibrium path exist.
An Information-Theoretic Framework to Measure the Dynamic Interaction between Neural Spike Trains
2021
Understanding the interaction patterns among simultaneous recordings of spike trains from multiple neuronal units is a key topic in neuroscience. However, an optimal approach of assessing these interactions has not been established, as existing methods either do not consider the inherent point process nature of spike trains or are based on parametric assumptions that may lead to wrong inferences if not met. This work presents a framework, grounded in the field of information dynamics, for the model-free, continuous-time estimation of both undirected (symmetric) and directed (causal) interactions between pairs of spike trains. The framework decomposes the overall information exchanged dynami…
Feature selection using support vector machines and bootstrap methods for ventricular fibrillation detection
2012
Early detection of ventricular fibrillation (VF) is crucial for the success of the defibrillation therapy in automatic devices. A high number of detectors have been proposed based on temporal, spectral, and time-frequency parameters extracted from the surface electrocardiogram (ECG), showing always a limited performance. The combination ECG parameters on different domain (time, frequency, and time-frequency) using machine learning algorithms has been used to improve detection efficiency. However, the potential utilization of a wide number of parameters benefiting machine learning schemes has raised the need of efficient feature selection (FS) procedures. In this study, we propose a novel FS…
Maximizing reading: pattern analysis to describe points of gaze
2006
As people read texts, their points of gaze can be described either as a sequence or as a pattern of dots. If reading fixations are visualized as a pattern and their duration is graphically attributed to the 3 rd dimension, image processing techniques can be employed to describe individual reading styles. Two reader groups of text editors and of University students were matching according to parametric tests. Yet they appeared to have marked inter-subject variability of fixation distribution when individual cases were considered. To illustrate this, we applied a simple "Coulomb law" - like model that takes both fixation duration and spacing into account. Further the image entropy filter was …
A Parallel Approach to HRTF Approximation and Interpolation Based on a Parametric Filter Model
2017
[EN] Spatial audio-rendering techniques using head-related transfer functions (HRTFs) are currently used in many different contexts such as immersive teleconferencing systems, gaming, or 3-D audio reproduction. Since all these applications usually involve real-time constraints, efficient processing structures for HRTF modeling and interpolation are necessary for providing real-time binaural audio solutions. This letter presents a parametric parallel model that allows us to perform HRTF filtering and interpolation efficiently from an input HRTF dataset. The resulting model, which is an adaptation from a recently proposed modeling technique, not only reduces the size of HRTF datasets signific…
Mixed-aspect fractal surfaces
2013
In order to provide accurate tools to model original surfaces in a Computer Aided Geometric Design context, we develop a formalism based on iterated function systems. This model enables us to represent both smooth and fractal free-form curves and surfaces. But, because of the self-similarity property underlying the iterated function systems, curves and surfaces can only have homogeneous roughness. The aim of our work was to elaborate a method to build parametric shapes (curves, surfaces, ...) with a non-uniform local aspect: every point is assigned a ''geometric texture'' that evolves continuously from a smooth to a rough aspect. The principle is to blend shapes with uniform aspects to defi…
Density-functional tight-binding for beginners
2009
This article is a pedagogical introduction to density-functional tight-binding (DFTB) method. We derive it from the density-functional theory, give the details behind the tight-binding formalism, and give practical recipes for parametrization: how to calculate pseudo-atomic orbitals and matrix elements, and especially how to systematically fit the short-range repulsions. Our scope is neither to provide a historical review nor to make performance comparisons, but to give beginner's guide for this approximate, but in many ways invaluable, electronic structure simulation method--now freely available as an open-source software package, hotbit.
Optical Fibers Enter a New Space-Time Era
2016
We show experimentally a new type of parametric instability associated with the original phenomenon of beam self-cleaning in multimode fibers. Our experimental results are in good agreement with numerical solutions of the Gross-Pitaevskii equation.
Multiscale Information Storage of Linear Long-Range Correlated Stochastic Processes
2019
Information storage, reflecting the capability of a dynamical system to keep predictable information during its evolution over time, is a key element of intrinsic distributed computation, useful for the description of the dynamical complexity of several physical and biological processes. Here we introduce a parametric approach which allows one to compute information storage across multiple timescales in stochastic processes displaying both short-term dynamics and long-range correlations (LRC). Our analysis is performed in the popular framework of multiscale entropy, whereby a time series is first "coarse grained" at the chosen timescale through low-pass filtering and downsampling, and then …
New Geometric Constraint Solving Formulation: Application to the 3D Pentahedron
2014
Geometric Constraint Solving Problems (GCSP) are nowadays routinely investigated in geometric modeling. The 3D Pentahedron problem is a GCSP defined by the lengths of its edges and the planarity of its quadrilateral faces, yielding to an under-constrained system of twelve equations in eighteen unknowns. In this work, we focus on solving the 3D Pentahedron problem in a more robust and efficient way, through a new formulation that reduces the underlying algebraic formulation to a well-constrained system of three equations in three unknowns, and avoids at the same time the use of placement rules that resolve the under-constrained original formulation. We show that geometric constraints can be …