Search results for "Canonical Correlation Analysis"
showing 5 items of 5 documents
Spectral alignment of multi-temporal cross-sensor images with automated kernel canonical correlation analysis
2015
In this paper we present an approach to perform relative spectral alignment between optical cross-sensor acquisitions. The proposed method aims at projecting the images from two different and possibly disjoint input spaces into a common latent space, in which standard change detection algorithms can be applied. The system relies on the regularized kernel canonical correlation analysis transformation (kCCA), which can accommodate nonlinear dependencies between pixels by means of kernel functions. To learn the projections, the method employs a subset of samples belonging to the unchanged areas or to uninteresting radiometric differences. Since the availability of ground truth information to p…
Performance of DEMETER calibration for rainfall forecasting purposes: Application to the July–August Sahelian rainfall
2008
International audience; This work assesses and compares the skill of direct and model-output-statistics (MOS) calibrated hindcasts of the July–August rainfall amounts for the dry period 1980–2000 over the Sahel issued from the Development of a European Multimodel Ensemble System for Seasonal to Interannual Prediction (DEMETER) experiment, with the aim to highlight among the simulated parameters, i.e., those potentially relevant for rainfall forecasts purposes. Three approaches were used: the DEMETER (1) direct rainfall, (2) MOS-calibrated rainfall, and (3) MOS-calibrated atmospheric dynamics and energy. Canonical correlation analyses (CCA) were employed in the two latter approaches to calib…
Online Detection and Removal of Eye Blink Artifacts from Electroencephalogram
2020
The most prominent type of artifact contaminating electroencephalogram (EEG)signals are the eyeblink (EB) artifacts, which could potentially lead tomisinterpretation of the EEG signal. Online detection and removal of eyeblink artifacts from EEG signals are essential in applications such a Brain-Computer Interfaces (BCI), neurofeedback and epilepsy diagnosis. In this thesis, algorithms that combine unsupervised eyeblink artifact detection (eADA) with enhanced Empirical Mode Decomposition (FastEMD) and Canonical Correlation Analysis (CCA) are proposed,i.e. FastEMD-CCA2 and FastCCA, to automatically identify eyeblink artifacts andremove them in an online setting. FastEMD-CCA2 and FastCCA have …
Eficiencia en la educación superior. Estudio empírico en universidades públicas de Colombia y España
2020
Resumen En las últimas décadas, las universidades de Iberoamérica han introducido nuevos esquemas de evaluación de calidad y rendición de cuentas, inspirados en el modelo de la nueva gestión pública (NGP). En este contexto, la eficiencia en el reparto de los fondos públicos y la obtención del máximo rendimiento posible son una prioridad. Así, medir la eficiencia en el sector público, y específicamente en la educación superior, se ha convertido en un desafío para la ciencia contable. El objetivo de este trabajo es una propuesta para el cálculo de índices de eficiencia con modelos de análisis envolvente de datos (DEA), introduciendo un paso previo a través del análisis de correlación canónica…
Analysis and assessment of trace element contamination in offshore sediments of the Augusta Bay (SE Sicily): A multivariate statistical approach base…
2014
Abstract An application of multivariate statistical methods is provided to identify anthropogenic contaminants and lithogenic elements in offshore sediments collected near the heavily industrialized Augusta Bay, Sicily. An exploratory statistical technique, based on canonical correlation analysis (CCA) and mixture density estimation approach, is used for distinguishing between natural and anthropogenic contributions of trace elements in the investigated sediments. Following the intensive industrialization of Augusta area, marine sediments reveal the severe impact of local anthropogenic activities for many elements (e.g. As, Cd, Hg, Pb, and Sb), which are considered very dangerous for the en…