Search results for "Matrices"

Unicity of biproportion

1994

International audience; The biproportion of S on margins of M is called the intern composition law, K: (S,M) -> X = K(S,M) / X = A S B. A and B are diagonal matrices, algorithmically computed, providing the respect of margins of M. Biproportion is an empirical concept. In this paper, the author shows that any algorithm used to compute a biproportion leads to the me result. Then the concept is unique and no longer empirical. Some special properties are also indicated.

Optimizing auditory images and distance metrics for self‐organizing timbre maps*

1996

Abstract The effect of using different auditory images and distance metrics on the final configuration of a self‐organized timbre map is examined by comparing distance matrices, obtained from simulations, with a similarity rating matrix, obtained using the same set of stimuli as in the simulations. Gradient images, which are intended to represent idealizations of physiological gradient maps in the auditory pathway, are constructed. The optimal auditory image and distance metric, with respect to the similarity rating data, are searched using the gradient method.

Two-loop Anomalous Dimensions of Heavy Baryon Currents in Heavy Quark Effective Theory

1996

We present results on the two-loop anomalous dimensions of the heavy baryon HQET currents $J=(q^TC\Gamma\tau q)\Gamma'Q$ with arbitrary Dirac matrices $\Gamma$ and $\Gamma'$. From our general result we obtain the two-loop anomalous dimensions for currents with quantum numbers of the ground state heavy baryons $\Lambda_Q$, $\Sigma_Q$ and $\Sigma_Q^*$. As a by-product of our calculation and as an additional check we rederive the known two-loop anomalous dimensions of mesonic scalar, pseudoscalar, vector, axial vector and tensor currents $(J=\bar q\Gamma q)$ in massless QCD as well as in HQET.

Flavor Symmetry and Vacuum Aligned Mass Textures

2006

21 pages, 2 figures.-- ArXiv pre-print available at: http://arxiv.org/abs/hep-ph/0609220

DISTATIS: The Analysis of Multiple Distance Matrices

2006

In this paper we present a generalization of classical multidimensional scaling called DISTATIS which is a new method that can be used to compare algorithms when their outputs consist of distance matrices computed on the same set of objects. The method first evaluates the similarity between algorithms using a coefficient called the RV coefficient. From this analysis, a compromise matrix is computed which represents the best aggregate of the original matrices. In order to evaluate the differences between algorithms, the original distance matrices are then projected onto the compromise. We illustrate this method with a "toy example" in which four different "algorithms" (two computer programs …

Low-Rank Tucker-2 Model for Multi-Subject fMRI Data Decomposition with Spatial Sparsity Constraint

2022

Tucker decomposition can provide an intuitive summary to understand brain function by decomposing multi-subject fMRI data into a core tensor and multiple factor matrices, and was mostly used to extract functional connectivity patterns across time/subjects using orthogonality constraints. However, these algorithms are unsuitable for extracting common spatial and temporal patterns across subjects due to distinct characteristics such as high-level noise. Motivated by a successful application of Tucker decomposition to image denoising and the intrinsic sparsity of spatial activations in fMRI, we propose a low-rank Tucker-2 model with spatial sparsity constraint to analyze multi-subject fMRI dat…

Indexed Two-Dimensional String Matching

2016

A fast BEM for the analysis of plates with bonded piezoelectric patches

2010

In this paper a fast boundary element method for the elastodynamic analysis of 3D structures with bonded piezoelectric patches is presented. The elastodynamic analysis is performed in the Laplace domain and the time history of the relevant quantities is obtained by inverse Laplace transform. The bonded patches are modelled using a semi-analytical state-space variational approach. The computational features of the technique, in terms of required storage memory and solution time, are improved by a fast solver based on the use of hierarchical matrices. The presented numerical results show the potential of the technique in the study of structural health monitoring (SHM) systems.

Structured methodology for selection of maintenance key performance indicators: Application to an oil refinery plant

2017

The novel contribution of the work is the proposal of a structured multi-step methodology that may support the Decision Maker (DM) in the measurement of maintenance performance by means of Maintenance Key Performance Indicators (MKPIs). To this aim, a multi-level hierarchical framework able to synthesize the most meaningful aspects affecting the maintenance results is designed. Then, MKPIs are selected from the literature, assigned to the hierarchical framework and ranked by an Analytic Hierarchy Process-based approach with incomplete comparison matrices. A mathematical model is finally formulated to select the optimal set of MKPIs. The methodology is implemented in an oil refinery plant an…

Normalised compression distance and evolutionary distance of genomic sequences: comparison of clustering results

2009

Genomic sequences are usually compared using evolutionary distance, a procedure that implies the alignment of the sequences. Alignment of long sequences is a time consuming procedure and the obtained dissimilarity results is not a metric. Recently, the normalised compression distance was introduced as a method to calculate the distance between two generic digital objects and it seems a suitable way to compare genomic strings. In this paper, the clustering and the non-linear mapping obtained using the evolutionary distance and the compression distance are compared, in order to understand if the two distances sets are similar.