412 research outputs found
SSA of biomedical signals: A linear invariant systems approach
Singular spectrum analysis (SSA) is considered from a linear invariant systems perspective. In this terminology, the extracted components are considered as outputs of a linear invariant system which corresponds to finite impulse response (FIR) filters. The number of filters is determined by the embedding dimension.We propose to explicitly define the frequency response of each filter responsible for the selection of informative components. We also introduce a subspace distance measure for clustering subspace models. We illustrate the methodology by analyzing lectroencephalograms (EEG).FCT - PhD scholarship (SFRH/BD/28404/2006)FCT - PhD scholarship (SFRH/BD/48775/2008
Exploiting low-rank approximations of kernel matrics in denoising applicationS
The eigendecomposition of a kernel matrix can present a
computational burden in many kernel methods. Nevertheless
only the largest eigenvalues and corresponding eigenvectors
need to be computed. In this work we discuss the
Nystrom low-rank approximations of the kernel matrix and
its applications in KPCA denoising tasks. Furthermore, the
low-rank approximations have the advantage of being related
with a smaller subset of the training data which constitute
then a basis of a subspace. In a common algebraic
framework we discuss the different approaches to compute
the basis. Numerical simulations concerning the denoising
are presented to compare the discussed approaches.info:eu-repo/semantics/publishedVersio
dAMUSE : a new tool for denoising and blind source separation
In this work a generalized version of AMUSE, called dAMUSE is proposed. The main modification consists in embedding the observed mixed signals in a high-dimensional feature space of delayed
coordinates. With the embedded signals a matrix pencil is formed and its generalized eigendecomposition is computed similar to the algorithm AMUSE. We show that in this case the uncorrelated
output signals are filtered versions of the unknown source signals. Further, denoising the data can be
achieved conveniently in parallel with the signal separation. Numerical simulations using artificially
mixed signals are presented to show the performance of the method. Further results of a heart rate
variability (HRV) study are discussed showing that the output signals are related with LF (low frequency) and HF (high frequency) fluctuations. Finally, an application to separate artifacts from 2D
NOESY NMR spectra and to denoise the reconstructed artefact-free spectra is presented also.info:eu-repo/semantics/publishedVersio
Denoising using local projective subspace methods
In this paper we present denoising algorithms for enhancing noisy signals based on Local ICA (LICA), Delayed AMUSE (dAMUSE)
and Kernel PCA (KPCA). The algorithm LICA relies on applying ICA locally to clusters of signals embedded in a high-dimensional
feature space of delayed coordinates. The components resembling the signals can be detected by various criteria like estimators of
kurtosis or the variance of autocorrelations depending on the statistical nature of the signal. The algorithm proposed can be applied
favorably to the problem of denoising multi-dimensional data. Another projective subspace denoising method using delayed coordinates
has been proposed recently with the algorithm dAMUSE. It combines the solution of blind source separation problems with denoising
efforts in an elegant way and proofs to be very efficient and fast. Finally, KPCA represents a non-linear projective subspace method that
is well suited for denoising also. Besides illustrative applications to toy examples and images, we provide an application of all algorithms
considered to the analysis of protein NMR spectra.info:eu-repo/semantics/publishedVersio
Feature Extraction and Classification of Biosignals - Emotion Valence Detection from EEG Signals
In thisworkavalencerecognitionsystembasedonelectroencephalogramsispresented.Theperformanceof
the systemisevaluatedfortwosettings:singlesubjects(intra-subject)andbetweensubjects(inter-subject).
The featureextractionisbasedonmeasuresofrelativeenergiescomputedinshorttimeintervalsandcertain
frequencybands.Thefeatureextractionisperformedeitheronsignalsaveragedoveranensembleoftrialsor
on single-trialresponsesignals.Thesubsequentclassificationstageisbasedonanensembleclassifier,i.e.a
random forestoftreeclassifiers.Theclassificationisperformedconsideringtheensembleaverageresponsesof
all subjects(inter-subject)orconsideringthesingle-trialresponsesofsinglesubjects(intra-subject).Applying
a properimportancemeasureoftheclassifier,featureeliminationhasbeenusedtoidentifythemostrelevant
features of the decision making.info:eu-repo/semantics/publishedVersio
Power spectrum of many impurities in a d-wave superconductor
Recently the structure of the measured local density of states power spectrum
of a small area of the \BSCCO (BSCCO) surface has been interpreted in terms of
peaks at an "octet" of scattering wave vectors determined assuming weak,
noninterfering scattering centers. Using analytical arguments and numerical
solutions of the Bogoliubov-de Gennes equations, we discuss how the
interference between many impurities in a d-wave superconductor alters this
scenario. We propose that the peaks observed in the power spectrum are not the
features identified in the simpler analyses, but rather "background" structures
which disperse along with the octet vectors. We further consider how our
results constrain the form of the actual disorder potential found in this
material.Comment: 5 pages.2 figure
Models for Enhanced Absorption in Inhomogeneous Superconductors
We discuss the low-frequency absorption arising from quenched inhomogeneity
in the superfluid density rho_s of a model superconductor. Such inhomogeneities
may arise in a high-T_c superconductor from a wide variety of sources,
including quenched random disorder and static charge density waves such as
stripes. Using standard classical methods for treating randomly inhomogeneous
media, we show that both mechanisms produce additional absorption at finite
frequencies. For a two-fluid model with weak mean-square fluctuations <(d
rho_s)^2 > in rho_s and a frequency-independent quasiparticle conductivity, the
extra absorption has oscillator strength proportional to the quantity <(d
rho_s)^2>/rho_s, as observed in some experiments. Similar behavior is found in
a two-fluid model with anticorrelated fluctuations in the superfluid and normal
fluid densities. The extra absorption typically occurs as a Lorentzian centered
at zero frequency. We present simple model calculations for this extra
absorption under conditions of both weak and strong fluctuations. The relation
between our results and other model calculations is briefly discussed
Research and innovation as a catalyst for food system transformation
Background: Food systems are associated with severe and persistent problems worldwide. Governance approaches aiming to foster sustainable transformation of food systems face several challenges due to the complex nature of food systems. Scope and approach: In this commentary we argue that addressing these governance challenges requires the development and adoption of novel research and innovation (R&I) approaches that will provide evidence to inform food system transformation and will serve as catalysts for change. We first elaborate on the complexity of food systems (transformation) and stress the need to move beyond traditional linear R&I approaches to be able to respond to persistent problems that affect food systems. Though integrated transdisciplinary approaches are promising, current R&I systems do not sufficiently support such endeavors. As such, we argue, we need strategies that trigger a double transformation - of food systems and of their R&I systems. Key Findings and Conclusions: Seizing the opportunities to transform R&I systems has implications for how research is done - pointing to the need for competence development among researchers, policy makers and society in general - and requires specific governance interventions that stimulate a systemic approach. Such interventions should foster transdisciplinary and transformative research agendas that stimulate portfolios of projects that will reinforce one another, and stimulate innovative experiments to shape conditions for systemic change. In short, a thorough rethinking of the role of R&I as well as how it is funded is a crucial step towards the development of the integrative policies that are necessary to engender systemic change - in the food system and beyond
The Dependence of the Superconducting Transition Temperature of Organic Molecular Crystals on Intrinsically Non-Magnetic Disorder: a Signature of either Unconventional Superconductivity or Novel Local Magnetic Moment Formation
We give a theoretical analysis of published experimental studies of the
effects of impurities and disorder on the superconducting transition
temperature, T_c, of the organic molecular crystals kappa-ET_2X and beta-ET_2X
(where ET is bis(ethylenedithio)tetrathiafulvalene and X is an anion eg I_3).
The Abrikosov-Gorkov (AG) formula describes the suppression of T_c both by
magnetic impurities in singlet superconductors, including s-wave
superconductors and by non-magnetic impurities in a non-s-wave superconductor.
We show that various sources of disorder lead to the suppression of T_c as
described by the AG formula. This is confirmed by the excellent fit to the
data, the fact that these materials are in the clean limit and the excellent
agreement between the value of the interlayer hopping integral, t_perp,
calculated from this fit and the value of t_perp found from angular-dependant
magnetoresistance and quantum oscillation experiments. If the disorder is, as
seems most likely, non-magnetic then the pairing state cannot be s-wave. We
show that the cooling rate dependence of the magnetisation is inconsistent with
paramagnetic impurities. Triplet pairing is ruled out by several experiments.
If the disorder is non-magnetic then this implies that l>=2, in which case
Occam's razor suggests that d-wave pairing is realised. Given the proximity of
these materials to an antiferromagnetic Mott transition, it is possible that
the disorder leads to the formation of local magnetic moments via some novel
mechanism. Thus we conclude that either kappa-ET_2X and beta-ET_2X are d-wave
superconductors or else they display a novel mechanism for the formation of
localised moments. We suggest systematic experiments to differentiate between
these scenarios.Comment: 18 pages, 5 figure
Levels and equivalence in credit and qualifications frameworks: Contrasting the prescribed and enacted curriculum in school and college
Drawing on data from an empirical study of three matched subjects in upper secondary school and further education college in Scotland, this article explores some of the factors that result in differences emerging from the translation of the prescribed curriculum into the enacted curriculum. We argue that these differences raise important questions about equivalences which are being promoted through the development of credit and qualifications frameworks. The article suggests that the standardisation associated with the development of a rational credit and qualifications framework and an outcomes-based prescribed curriculum cannot be achieved precisely because of the multiplicity that emerges from the practices of translation
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