Search results for "Convolution"

Nonradial Hormander algebras of several variables and convolution operators

2001

A characterization of the closed principal ideals in nonradial Hormander algebras of holomorphic functions of several variables in terms of the behaviour of the generator is obtained. This result is applied to study the range of convolution operators and ultradifferential operators on spaces of quasianalytic functions of Beurling type. Contrary to what is known to happen in the case of non-quasianalytic functions, an ultradistribution on a space of quasianalytic functions is constructed such that the range of the operator does not contain the real analytic functions. Let u, v : R → R be continuous, non-negative and even functions which are increasing on the positive real numbers. We assume …

A characterization of riesz operators

1987

Parton distributions in a constituent quark scenario

1999

A simple picture of the constituent quark as a composite system of point-like partons is used to construct the unpolarized and polarized parton distributions by a convolution between constituent quark momentum distributions and constituent quark structure functions. We achieve good agreement with experiments in the unpolarized, as well as, in the polarized case. When our results are compared with similar calculations using non-composite constituent quarks, the accord with the experiments of the present scheme is impressive. We conclude that DIS data are consistent with a low energy scenario dominated by composite constituents of the nucleon.

Towards a unified picture of constituent and current quarks

1997

Using a simple picture of the constituent quark as a composite system of point-like partons, we construct the parton distributions by a convolution between constituent quark momentum distributions and constituent quark structure functions. We evaluate the latter at a low hadronic scale with updated phenomenological information, and we build the momentum distributions using well-known quark models. The resulting parton distributions and structure functions are evolved to the experimental scale and good agreement with the available DIS data is achieved. When compared with a similar calculation using non-composite constituent quarks, the accord with experiment of the present calculation become…

Use of machine learning approaches to improve non-invasive skin melanoma diagnostic method in spectral range 450 - 950nm

2020

Non-invasive skin cancer diagnostic methods develop rapidly thanks to Deep Learning and Convolutional Neural Networks (CNN). Currently, two types of diagnostics are popular: (a) using single image taken under white illumination and (b) using multiple images taken in narrow spectral bands. The first method is easier to implement, but it is limited in accuracy. The second method is more sensitive, because it is possible to use illumination considering the absorption bands of the skin chromophores and the optical properties of the skin. Currently CNN use a single white light image, due to the availability of large datasets with lesion images. Since CNN processing and analysis requires a large …

Convolutional Matrix Factorization for Recommendation Explanation

2018

In this paper, we introduce a novel recommendation model, which harnesses a convolutional neural network to mine meaningful information from customer reviews, and integrates it with matrix factorization algorithm seamlessly. It is a valid method to improve the transparency of CF algorithms.

Fractional model of concrete hereditary viscoelastic behaviour

2016

The evaluation of creep effects in concrete structures is addressed in the literature using different predictive models, supplied by specific codes, and applying the concepts of linear viscoelastic theory with ageing. The expressions used in the literature are mainly based on exponential laws, which are introduced in the integral expression of the Boltzmann principle; this approach leads to the need of finding approximated numerical solutions of the viscoelastic response. In this study, the hereditary fractional viscoelastic model is applied to concrete elements, underlining the convenience of using creep or relaxation functions expressed by power laws. The full reciprocal character of cree…

Segmentation-Free Estimation of Aortic Diameters from MRI Using Deep Learning

2021

Accurate and reproducible measurements of the aortic diameters are crucial for the diagnosis of cardiovascular diseases and for therapeutic decision making. Currently, these measurements are manually performed by healthcare professionals, being time consuming, highly variable, and suffering from lack of reproducibility. In this work we propose a supervised deep-learning method for the direct estimation of aortic diameters. The approach is devised and tested over 100 magnetic resonance angiography scans without contrast agent. All data was expert-annotated at six aortic locations typically used in clinical practice. Our approach makes use of a 3D+2D convolutional neural network (CNN) that ta…

On the Robustness of Deep Features for Audio Event Classification in Adverse Environments

2018

Deep features, responses to complex input patterns learned within deep neural networks, have recently shown great performance in image recognition tasks, motivating their use for audio analysis tasks as well. These features provide multiple levels of abstraction which permit to select a sufficiently generalized layer to identify classes not seen during training. The generalization capability of such features is very useful due to the lack of complete labeled audio datasets. However, as opposed to classical hand-crafted features such as Mel-frequency cepstral coefficients (MFCCs), the performance impact of having an acoustically adverse environment has not been evaluated in detail. In this p…

LaDy: Software for assessing local landscape diversity profiles of raster land cover maps using geographic windows

2003

Landscape ecology starts from the assumption that diversity and spatial arrangement of ecosystem mosaics have ecological implications and tries to understand the interactions between diversity and structure of large spatially heterogeneous areas and their ecological functions. These assumptions imply effective use of earth observation techniques and geographic information systems, enabling a global view of the landscape mosaics. In this paper, a software, LaDy (Landscape Diversity Software), for computing Re´nyi’s local landscape diversity profile on raster land cover maps is presented. LaDy is based on the use of Merchant’s adaptive geographic window, which is designed to operate on a neig…