Search results for "Algorithms"

Measuring frequency domain granger causality for multiple blocks of interacting time series

2011

In the past years, several frequency-domain causality measures based on vector autoregressive time series modeling have been suggested to assess directional connectivity in neural systems. The most followed approaches are based on representing the considered set of multiple time series as a realization of two or three vector-valued processes, yielding the so-called Geweke linear feedback measures, or as a realization of multiple scalar-valued processes, yielding popular measures like the directed coherence (DC) and the partial DC (PDC). In the present study, these two approaches are unified and generalized by proposing novel frequency-domain causality measures which extend the existing meas…

Adaptive independent vector analysis for multi-subject complex-valued fMRI data.

2017

Abstract Background Complex-valued fMRI data can provide additional insights beyond magnitude-only data. However, independent vector analysis (IVA), which has exhibited great potential for group analysis of magnitude-only fMRI data, has rarely been applied to complex-valued fMRI data. The main challenges in this application include the extremely noisy nature and large variability of the source component vector (SCV) distribution. New method To address these challenges, we propose an adaptive fixed-point IVA algorithm for analyzing multiple-subject complex-valued fMRI data. We exploited a multivariate generalized Gaussian distribution (MGGD)- based nonlinear function to match varying SCV dis…

A Grid Enabled Parallel Hybrid Genetic Algorithm for SPN

2004

This paper presents a combination of a parallel Genetic Algorithm (GA) and a local search methodology for the Steiner Problem in Networks (SPN). Several previous papers have proposed the adoption of GAs and others metaheuristics to solve the SPN demonstrating the validity of their approaches. This work differs from them for two main reasons: the dimension and the features of the networks adopted in the experiments and the aim from which it has been originated. The reason that aimed this work was namely to assess deterministic and computationally inexpensive algorithms which can be used in practical engineering applications, such as the multicast transmission in the Internet. The large dimen…

Surrogate Data Analysis for Assessing the Significance of the Coherence Function

2004

In cardiovascular variability analysis, the significance of the coupling between two time series is commonly assessed by setting a threshold level in the coherence function. While traditionally used statistical tests consider only the parameters of the adopted estimator, the required zero-coherence level may be affected by some features of the observed series. In this study, three procedures, based on the generation of surrogate series sharing given properties with the original but being structurally uncoupled, were considered: independent identically distributed (IID), Fourier transform (FT), and autoregressive (AR). IID surrogates maintained the distribution of the original series, while …

Distributed multi-objective optimization methods for shape design using evolutionary algorithms and game strategies

2012

Complexity of operations on cofinite languages

2010

International audience; We study the worst case complexity of regular operation on cofinite languages (i.e., languages whose complement is finite) and provide algorithms to compute efficiently the resulting minimal automata.

Bandwidth Resource Management for Neural Signal Telemetry

2009

Recent advances in modern neurocomputing have shown the utmost necessity of wireless communication systems that allow real-time (RT) monitoring of neural signals meeting several requirements such as source compression and high fidelity of the received signal. Neural recordings require multielectrode probes with up to hundreds of electrodes and transmission of signals wirelessly over a limited bandwidth (BW). In this paper, a RT resource management algorithm is proposed so that adequate source compression is applied to each channel in order to fit them into the available BW. Performance of the algorithm is analyzed using dynamically changing BW and neural recordings with different neural act…

Predictive Toxicology of Cobalt Nanoparticles and Ions: Comparative In Vitro Study of Different Cellular Models Using Methods of Knowledge Discovery …

2011

The toxicological effects of cobalt nanoparticles (Co-NPs) aggregates were examined and compared with those of cobalt ions (Co-ions) using six different cell lines representing lung, liver, kidney, intestine, and the immune system. Dose-response curves were studied in the concentration range of 0.05-1.0 mM, employing 3-(4,5-dimethylthiazol-2-Yl)-2,5-diphenyltetrazolium bromide test, neutral red, and Alamar blue as end point assays following exposures for 48 and 72 h. Data analysis and predictive modeling of the obtained data sets were executed by employing a decision tree model (J48), where training and validation were carried out by an iterative process. It was established, as expected, th…

Disconnected Graph Layout and the Polyomino Packing Approach

2002

Conference name: GD: International Symposium on Graph Drawing 9th International Symposium Date of Conference: 23–26 September 2001 We review existing algorithms and present a new approach for layout of disconnected graphs. The new approach is based on polyomino representation of components as opposed to rectangles. The parameters of our algorithm and their influence on the drawings produced as well as a variation of the algorithm for multiple pages are discussed. We also analyze our algorithm both theoretically and experimentally and compare it with the existing ones. The new approach produces much more compact and uniform drawings than previous methods. © Springer-Verlag Berlin Heidelberg …

Quantification of melanin and hemoglobin in humain skin from multispectral image acquisition: use of a neuronal network combined to a non-negative ma…

2012

International audience; This article presents a multispectral imaging system which, coupled with a neural network-based algorithm, reconstructs reflectance cubes. The reflectance spectra are obtained using artificial neural-netwok reconstruction which generates reflectance cubes from acquired multispectral images. Then, a blind source separation algorithm based on Non-negative Matrix Factorization is used for the decomposition of human skin absorption spectra in its main pigments: melanin and hemoglobin. The analysis is performed on reflectance spectra. The implemented source separation algorithm is based on a multiplicative coefficient upload. The goal is to represent a given spectrum as t…