Search results for "Numerical"

LOCAL CONTROL OF SOUND IN STOCHASTIC DOMAINS BASED ON FINITE ELEMENT MODELS

2011

A numerical method for optimizing the local control of sound in a stochastic domain is developed. A three-dimensional enclosed acoustic space, for example, a cabin with acoustic actuators in given locations is modeled using the finite element method in the frequency domain. The optimal local noise control signals minimizing the least square of the pressure field in the silent region are given by the solution of a quadratic optimization problem. The developed method computes a robust local noise control in the presence of randomly varying parameters such as variations in the acoustic space. Numerical examples consider the noise experienced by a vehicle driver with a varying posture. In a mod…

Higher-order Nonnegative CANDECOMP/PARAFAC Tensor Decomposition Using Proximal Algorithm

2019

Tensor decomposition is a powerful tool for analyzing multiway data. Nowadays, with the fast development of multisensor technology, more and more data appear in higherorder (order > 4) and nonnegative form. However, the decomposition of higher-order nonnegative tensor suffers from poor convergence and low speed. In this study, we propose a new nonnegative CANDECOM/PARAFAC (NCP) model using proximal algorithm. The block principal pivoting method in alternating nonnegative least squares (ANLS) framework is employed to minimize the objective function. Our method can guarantee the convergence and accelerate the computation. The results of experiments on both synthetic and real data demonstrate …

Synchronization of hidden chaotic attractors on the example of radiophysical oscillators

2017

In the present paper we consider the problem of synchronization of hidden and self-excited attractors in the context of application to a system of secure communication. The system of two coupled Chua models was studied. Complete synchronization was observed as for self-excited, as hidden attractors. Beside it for hidden attractors some special type of dynamic was revealed.

The Tucker tensor decomposition for data analysis: capabilities and advantages

2022

Tensors are powerful multi-dimensional mathematical objects, that easily embed various data models such as relational, graph, time series, etc. Furthermore, tensor decomposition operators are of great utility to reveal hidden patterns and complex relationships in data. In this article, we propose to study the analytical capabilities of the Tucker decomposition, as well as the differences brought by its major algorithms. We demonstrate these differences through practical examples on several datasets having a ground truth. It is a preliminary work to add the Tucker decomposition to the Tensor Data Model, a model aiming to make tensors data-centric, and to optimize operators in order to enable…

Sparse nonnegative tensor decomposition using proximal algorithm and inexact block coordinate descent scheme

2021

Nonnegative tensor decomposition is a versatile tool for multiway data analysis, by which the extracted components are nonnegative and usually sparse. Nevertheless, the sparsity is only a side effect and cannot be explicitly controlled without additional regularization. In this paper, we investigated the nonnegative CANDECOMP/PARAFAC (NCP) decomposition with the sparse regularization item using l1-norm (sparse NCP). When high sparsity is imposed, the factor matrices will contain more zero components and will not be of full column rank. Thus, the sparse NCP is prone to rank deficiency, and the algorithms of sparse NCP may not converge. In this paper, we proposed a novel model of sparse NCP w…

On the effectiveness of numerical simulation in the prediction of profile distorsion in extrusion

2005

Experimental campaign to assess numerical simulation of tool wear in orthogonal cutting

2007

Recommendations of the LHC Dark Matter Working Group: Comparing LHC searches for dark matter mediators in visible and invisible decay channels and ca…

2019

Physics of the Dark Universe 26, 100377 (2019). doi:10.1016/j.dark.2019.100377

Asiakasvaatimusten priorisointi osana vaatimustenhallintaa

2013

Asikainen, Markus Petteri Asiakasvaatimusten priorisointi osana vaatimustenhallintaa Jyväskylä: Jyväskylän yliopisto, 2013, 24 s. Tietojärjestelmätiede, kandidaatin tutkielma Ohjaaja: Jauhiainen, Eliisa Ohjelmistotuotannossa asiakasvaatimukset määrittävät ne ohjelmiston edelly-tykset ja rajoitukset, joiden avulla ohjelmisto pyrkii täyttämään heidän tarpei-taan reaalimaailmassa. Asiakasvaatimuksia tunnistetaan ja hallitaan vaatimus-tenhallintaprosessissa, jonka tavoitteena on varmistaa, että kehitettävä ohjelmis-to täyttää asiakkaan ja käyttäjän vaatimukset ja odotukset. Ohjelmistoprojek-teissa tunnistetaan usein huomattavasti enemmän vaatimuksia kuin ohjelmis-ton toteuttamisessa voidaan huo…

Reliable Outer Bounds for the Dual Simplex Algorithm with Interval Right-hand Side

2013

International audience; In this article, we describe the reliable computation of outer bounds for linear programming problems occuring in linear relaxations derived from the Bernstein polynomials. The computation uses interval arithmetic for the Gauss-Jordan pivot steps on a simplex tableau. The resulting errors are stored as interval right hand sides. Additionally, we show how to generate a start basis for the linear programs of this type. We give details of the implementation using OpenMP and comment on numerical experiments.