Search results for "Vector"
showing 10 items of 2660 documents
Physics-aware Gaussian processes in remote sensing
2018
Abstract Earth observation from satellite sensory data poses challenging problems, where machine learning is currently a key player. In recent years, Gaussian Process (GP) regression has excelled in biophysical parameter estimation tasks from airborne and satellite observations. GP regression is based on solid Bayesian statistics, and generally yields efficient and accurate parameter estimates. However, GPs are typically used for inverse modeling based on concurrent observations and in situ measurements only. Very often a forward model encoding the well-understood physical relations between the state vector and the radiance observations is available though and could be useful to improve pre…
A novel cell wall protein specific to the mycelial form of Yarrowia lipolytica.
1996
A cDNA clone specifying a cell wall protein was isolated from a Yarrowia lipolytica cDNA library. The cDNA library was constructed in the expression vector lambda gt 11, with the RNA isolated from actively growing mycelial cells. The deduced amino acid sequence shows that the encoded protein contains an N-terminal hydrophobic signal peptide. We have designated this protein YWP1 for Yarrowia lipolytica cell Wall Protein. Northern hybridization identified YWP1 transcript only when Y. lipolytica was growing in the mycelial form. The encoded protein seems to be covalently bound to the glucan cell wall since it is not released from the cell walls by sodium dodecyl sulphate extraction, but it is …
A probabilistic compressive sensing framework with applications to ultrasound signal processing
2019
Abstract The field of Compressive Sensing (CS) has provided algorithms to reconstruct signals from a much lower number of measurements than specified by the Nyquist-Shannon theorem. There are two fundamental concepts underpinning the field of CS. The first is the use of random transformations to project high-dimensional measurements onto a much lower-dimensional domain. The second is the use of sparse regression to reconstruct the original signal. This assumes that a sparse representation exists for this signal in some known domain, manifested by a dictionary. The original formulation for CS specifies the use of an l 1 penalised regression method, the Lasso. Whilst this has worked well in l…
Cell-average WENO with progressive order of accuracy close to discontinuities with applications to signal processing
2020
In this paper we translate to the cell-average setting the algorithm for the point-value discretization presented in S. Amat, J. Ruiz, C.-W. Shu, D. F. Y\'a\~nez, A new WENO-2r algorithm with progressive order of accuracy close to discontinuities, submitted to SIAM J. Numer. Anal.. This new strategy tries to improve the results of WENO-($2r-1$) algorithm close to the singularities, resulting in an optimal order of accuracy at these zones. The main idea is to modify the optimal weights so that they have a nonlinear expression that depends on the position of the discontinuities. In this paper we study the application of the new algorithm to signal processing using Harten's multiresolution. Se…
Adaptive motion estimation and video vector quantization based on spatiotemporal non-linearities of human perception
1997
The two main tasks of a video coding system are motion estimation and vector quantization of the signal. In this work a new splitting criterion to control the adaptive decomposition for the non-uniform optical flow estimation is exposed. Also, a novel bit allocation procedure is proposed for the quantization of the DCT transform of the video signal. These new approaches are founded on a perception model that reproduce the relative importance given by the human visual system to any location in the spatial frequency, temporal frequency and amplitude domain of the DCT transform. The experiments show that the proposed procedures behave better than their equivalent (fixed-block-size motion estim…
An Automatic System for the Analysis and Classification of Human Atrial Fibrillation Patterns from Intracardiac Electrograms
2008
This paper presents an automatic system for the analysis and classification of atrial fibrillation (AF) patterns from bipolar intracardiac signals. The system is made up of: 1) a feature- extraction module that defines and extracts a set of measures potentially useful for characterizing AF types on the basis of their degree of organization; 2) a feature-selection module (based on the Jeffries-Matusita distance and a branch and bound search algorithm) identifying the best subset of features for discriminating different AF types; and 3) a support vector machine technique-based classification module that automatically discriminates the AF types according to the Wells' criteria. The automatic s…
Support Vector Machines Framework for Linear Signal Processing
2005
This paper presents a support vector machines (SVM) framework to deal with linear signal processing (LSP) problems. The approach relies on three basic steps for model building: (1) identifying the suitable base of the Hilbert signal space in the model, (2) using a robust cost function, and (3) minimizing a constrained, regularized functional by means of the method of Lagrange multipliers. Recently, autoregressive moving average (ARMA) system identification and non-parametric spectral analysis have been formulated under this framework. The generalized, yet simple, formulation of SVM LSP problems is particularized here for three different issues: parametric spectral estimation, stability of I…
Search for Isovector Valence-Shell Excitations in 140 Nd and 142 Sm via Coulomb excitation reactions of radioactive ion beams
2018
Projectile Coulomb excitation experiments were performed at HIE-ISOLDE at CERN with the radioactive ion beams of 140Nd and 142Sm. Ions with an energy of 4:62 MeV/A were impinging on a 1.45 mg/cm2 thick 208Pb target. The γ-rays depopulating the Coulomb-excited states were recorded by the HPGe-array MINIBALL and scattered particles were detected by a double-sided silicon strip detector. Experimental intensities were used for the determination of electromagnetic transition matrix elements. A preliminary result of the B(M1; 2+3 → 2+1) of 140Nd and an upper limit for the case of 142Sm are revealing the main fragments of the proton-neutron mixed-symmetry 2+1;ms states.
Comparison of Intensity-based B-splines and Point-to-Pixel Tracking Techniques for Motion Reduction in Optical Mapping
2016
Suppression of motion artifacts (MA) in cardiac optical mapping usually requires uncoupling of cardiac contraction by restriction techniques, which are known to have important effects on cardiac physiology deteriorating the quality of acquisitions and their interpretation. In this study, we propose to assess the performance of two independent intensity-based post-processing strategies to minimize MAs during registration. A point-to-pixel block-matching classical similarity-based tracking with displacement interpolation is compared to a well-known non-rigid registration algorithm where the deformation field is obtained using cubic splines. Both strategies were tested on synthetic and real op…
Detection of a reservoir water level using shape similarity metrics
2017
The matching between reservoirs’ water edge and digital elevation model’s (DEM) contour lines allowed determining the water level at the acquisition date of satellite images. A preliminary study was conducted on the Castello dam (Magazzolo Lake), between Alessandria della Rocca and Bivona (Agrigento, south-Italy). The accuracy assessment of the technique was than evaluated from the comparison between classified and reference objects using similarity metrics about the shape, theme, edge and position, through the plugin STEP of open source software GIS. Moreover, an independent GIS technique was implemented to evaluate the water level, based on a distances’ array between existing contour line…