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