Search results for " pattern"
showing 10 items of 2245 documents
Signal-to-noise ratio in reproducing kernel Hilbert spaces
2018
This paper introduces the kernel signal-to-noise ratio (kSNR) for different machine learning and signal processing applications}. The kSNR seeks to maximize the signal variance while minimizing the estimated noise variance explicitly in a reproducing kernel Hilbert space (rkHs). The kSNR gives rise to considering complex signal-to-noise relations beyond additive noise models, and can be seen as a useful signal-to-noise regularizer for feature extraction and dimensionality reduction. We show that the kSNR generalizes kernel PCA (and other spectral dimensionality reduction methods), least squares SVM, and kernel ridge regression to deal with cases where signal and noise cannot be assumed inde…
Statistical analysis of noise levels in urban areas
1991
Abstract Environmental noise measurements have been carried out during recent years in different cities and locations of Spain. The noise levels have been continuously sampled over 24 h periods using a noise level analyzer. The data contained in this paper represent a total of 4200 measurement hours. All the information has been used to investigate the time patterns of the noise levels under a wide range of different conditions and to study the relationships between several noise descriptors in urban areas.
Cross-diffusion driven instability for a Lotka-Volterra competitive reaction-diffusion system
2008
In this work we investigate the possibility of the pattern formation for a reaction-di®usion system with nonlinear di®usion terms. Through a linear sta- bility analysis we ¯nd the conditions which allow a homogeneous steady state (stable for the kinetics) to become unstable through a Turing mechanism. In particular, we show how cross-di®usion e®ects are responsible for the initiation of spatial patterns. Finally, we ¯nd a Fisher amplitude equation which describes the weakly nonlinear dynamics of the system near the marginal stability.
Nonlinear higher-order polariton topological insulator
2020
We address the resonant response and bistability of the exciton-polariton corner states in a higher-order nonlinear topological insulator realized with kagome arrangement of microcavity pillars. Such states are resonantly excited and exist due to the balance between pump and losses, on the one hand, and between nonlinearity and dispersion in inhomogeneous potential landscape, on the other hand, for pump energy around eigen-energies of corresponding linear localized modes. Localization of the nonlinear corner states in a higher-order topological insulator can be efficiently controlled by tuning pump energy. We link the mechanism of corner state formation with symmetry of the truncated kagome…
Edge detection insensitive to changes of illumination in the image
2010
In this paper we present new edge detection algorithms which are motivated by recent developments on edge-adapted reconstruction techniques [F. Arandiga, A. Cohen, R. Donat, N. Dyn, B. Matei, Approximation of piecewise smooth functions and images by edge-adapted (ENO-EA) nonlinear multiresolution techniques, Appl. Comput. Harmon. Anal. 24 (2) (2008) 225-250]. They are based on comparing local quantities rather than on filtering and thresholding. This comparison process is invariant under certain transformations that model light changes in the image, hence we obtain edge detection algorithms which are insensitive to changes in illumination.
Propagation pattern analysis during atrial fibrillation based on sparse modeling.
2012
In this study, sparse modeling is introduced for the estimation of propagation patterns in intracardiac atrial fibrillation (AF) signals. The estimation is based on the partial directed coherence function, derived from fitting a multivariate autoregressive model to the observed signal using least-squares (LS) estimation. The propagation pattern analysis incorporates prior information on sparse coupling as well as the distance between the recording sites. Two optimization methods are employed for estimation of the model parameters, namely, the adaptive group least absolute selection and shrinkage operator (aLASSO), and a novel method named the distance-adaptive group LASSO (dLASSO). Using si…
Propagation pattern analysis during atrial fibrillation based on the adaptive group LASSO.
2012
The present study introduces sparse modeling for the estimation of propagation patterns in intracardiac atrial fibrillation (AF) signals. The estimation is based on the partial directed coherence (PDC) function, derived from fitting a multivariate autoregressive model to the observed signals. A sparse optimization method is proposed for estimation of the model parameters, namely, the adaptive group least absolute selection and shrinkage operator (aLASSO). In simulations aLASSO was found superior to the commonly used least-squares (LS) estimation with respect to estimation performance. The normalized error between the true and estimated model parameters dropped from 0.200.04 for LS estimatio…
How to standardize (if you must)
2017
In many situations we are interested in appraising the value of a certain characteristic for a given individual relative to the context in which this value is observed. In recent years this problem has become prominent in the evaluation of scientific productivity and impact. A popular approach to such relative valuations consists in using percentile ranks. This is a purely ordinal method that may sometimes lead to counterintuitive appraisals, in that it discards all information about the distance between the raw values within a given context. By contrast, this information is partly preserved by using standardization, i.e., by transforming the absolute values in such a way that, within the s…
Balamane: Variations on a Noisy Ground
2020
This contribution concentrates on a discussion of four conceptual keywords – Helmut, Sunglasses, Water, Language – which we explore as semiotic variations on a ground. This approach to the contradictory everyday realities of the touristic setting in Mallorca is the result of our (self-)critical reflections on how to write about language, migration, encounters, the normal and the liminal in the party tourism spot – and on how to give a (personal) insight into the world of contradictions at the Ballermann. We are considerably grateful to our research colleagues Angelika Mietzner and Janine Traber, with whom we have been working on the complex entanglements of tourism and migration since 2016 …
Fitting flavour symmetries: the case of two-zero neutrino mass textures
2018
We present a numeric method for the analysis of the fermion mass matrices predicted in flavour models. The method does not require any previous algebraic work, it offers a $\chi^{2}$ comparison test and an easy estimate of confidence intervals. It can also be used to study the stability of the results when the predictions are disturbed by small perturbations. We have applied the method to the case of two-zero neutrino mass textures using the latest available fits on neutrino oscillations, derived the available parameter space for each texture and compared them. Textures $A_{1}$ and $A_{2}$ seem favoured because they give a small $\chi^{2}$, allow for large regions in parameter space and giv…