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Titre : Mathematics and digital signal processing Type de document : Monographie Auteurs : Pavel Lyakhov, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 180 p. Format : 16 x 23 cm ISBN/ISSN/EAN : 978-3-0365-1475-8 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] apprentissage automatique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] dégradation du signal
[Termes IGN] entropie maximale
[Termes IGN] filtre adaptatif
[Termes IGN] filtre numérique
[Termes IGN] modélisation 3D
[Termes IGN] qualité du signal
[Termes IGN] rapport signal sur bruit
[Termes IGN] signal numérique
[Termes IGN] transformation en ondelettesRésumé : (éditeur) Modern computer technology has opened up new opportunities for the development of digital signal processing methods. The applications of digital signal processing have expanded significantly and today include audio and speech processing, sonar, radar, and other sensor array processing, spectral density estimation, statistical signal processing, digital image processing, signal processing for telecommunications, control systems, biomedical engineering, and seismology, among others. This Special Issue is aimed at wide coverage of the problems of digital signal processing, from mathematical modeling to the implementation of problem-oriented systems. The basis of digital signal processing is digital filtering. Wavelet analysis implements multiscale signal processing and is used to solve applied problems of de-noising and compression. Processing of visual information, including image and video processing and pattern recognition, is actively used in robotic systems and industrial processes control today. Improving digital signal processing circuits and developing new signal processing systems can improve the technical characteristics of many digital devices. The development of new methods of artificial intelligence, including artificial neural networks and brain-computer interfaces, opens up new prospects for the creation of smart technology. This Special Issue contains the latest technological developments in mathematics and digital signal processing. The stated results are of interest to researchers in the field of applied mathematics and developers of modern digital signal processing systems. Note de contenu : 1- Analysis of the quantization noise in discrete wavelet transform filters for 3D medical imaging
2- Maximum correntropy criterion based l1-iterative Wiener filter for sparse channel estimation robust to impulsive noise
3- Development of classification algorithms for the detection of postures using non-marker-based motion capture systems
4- Three-dimensional (3D) model-based lower limb stump automatic orientation
5- Improving calculation accuracy of digital filters based on finite field algebra
6- Multiresolution speech enhancement based on proposed circular nested microphone array in combination with sub-band affine projection algorithm
7- Classification of hydroacoustic signals based on harmonic wavelets and a deep learning artificial intelligence system
8- Quantification of the feedback regulation by digital signal analysis methods: Application to blood pressure control efficacy
9- Wood defect detection based on depth extreme learning machine
10- A division algorithm in a redundant residue number system using fractionsNuméro de notice : 28684 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-0365-1475-8 En ligne : https://doi.org/10.3390/books978-3-0365-1475-8 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99983
Titre : Polynomials: special polynomials and number-theoretical applications Type de document : Monographie Auteurs : Ákos Pintér, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 154 p. Format : 17 x 25 cm ISBN/ISSN/EAN : 978-3-0365-0819-1 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Mathématique
[Termes IGN] distribution binomiale
[Termes IGN] équation polynomiale
[Termes IGN] fonction de base radiale
[Termes IGN] formule d'Euler
[Termes IGN] interpolation polynomiale
[Termes IGN] théorème de Bernstein
[Termes IGN] trigonométrieRésumé : (éditeur) Polynomials play a crucial role in many areas of mathematics including algebra, analysis, number theory, and probability theory. They also appear in physics, chemistry, and economics. Especially extensively studied are certain infinite families of polynomials. Here, we only mention some examples: Bernoulli, Euler, Gegenbauer, trigonometric, and orthogonal polynomials and their generalizations. There are several approaches to these classical mathematical objects. This Special Issue presents nine high quality research papers by leading researchers in this field. I hope the reading of this work will be useful for the new generation of mathematicians and for experienced researchers as well. Note de contenu : 1- Two variables Shivley’s matrix polynomial
2- Some symmetric identities for degenerate Carlitz-type (p, q)-Euler numbers and polynomials
3- Symmetric identities for Carlitz-type higher-order degenerate (p, q)-Euler numbers and polynomials
4- Durrmeyer-type generalization of parametric Bernstein operators
5- A collocation method using radial polynomials for solving partial differential equations
6- On the decomposability of the linear combinations of Euler polynomials with odd degrees
7- Structure of approximate roots based on symmetric properties of (p, q)-cosine and (p, q)-sine Bernoulli polynomials
8- Explicit properties of q-cosine and q-sine Euler polynomials containing symmetric structures
9- Certain results for the twice-iterated 2D q-Appell polynomialsNuméro de notice : 28632 Affiliation des auteurs : non IGN Thématique : MATHEMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-0365-0819-1 En ligne : https://doi.org/10.3390/books978-3-0365-0819-1 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99635 Spatial characterization and distribution modelling of Ensete ventricosum (wild and cultivated) in Ethiopia / Meron Awoke Eshetae in Geocarto international, vol 36 n° 1 ([01/01/2021])
[article]
Titre : Spatial characterization and distribution modelling of Ensete ventricosum (wild and cultivated) in Ethiopia Type de document : Article/Communication Auteurs : Meron Awoke Eshetae, Auteur ; Binyam Tesfaw Hailu, Auteur ; Sebsebe Demissew, Auteur Année de publication : 2021 Article en page(s) : pp 60 - 75 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] distribution spatiale
[Termes IGN] données de terrain
[Termes IGN] données environnementales
[Termes IGN] entropie maximale
[Termes IGN] Ethiopie
[Termes IGN] Musa (genre)
[Termes IGN] surface cultivéeRésumé : (Auteur) Enset (Ensete ventricosum) feeds around 20 million people in Ethiopia and is arguably the most important crop for food security and rural livelihoods in the country. Therefore, it is significant to know its spatial characterization and distribution in the country. We use spatial overlay analysis and the maximum entropy (MaxEnt) model for characterizing and modelling, respectively. Inputs for the model include 26 environmental variables—19 bioclimatic and seven biophysical—in addition to the geospatial location of enset field data. The model result was validated using Receiver Operating Characteristic curve method and the area under the curve (AUC) with 0.842 for cultivated enset and 0.760 (wild enset). The highest prediction (>0.5) of both varieties occurred in the southwestern, south-central and north-eastern parts of Ethiopia—17,293.67 km2 (cultivated) and 40,402 km2 (wild) area. The presence of both enset is probabilistically higher at the tropic-cool/sub-humid Agroecological Zones. Numéro de notice : A2021-051 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1588392 Date de publication en ligne : 10/06/2020 En ligne : https://doi.org/10.1080/10106049.2019.1588392 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96773
in Geocarto international > vol 36 n° 1 [01/01/2021] . - pp 60 - 75[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2021011 RAB Revue Centre de documentation En réserve L003 Disponible Hyperspectral unmixing using orthogonal sparse prior-based autoencoder with hyper-laplacian loss and data-driven outlier detection / Zeyang Dou in IEEE Transactions on geoscience and remote sensing, vol 58 n° 9 (September 2020)
[article]
Titre : Hyperspectral unmixing using orthogonal sparse prior-based autoencoder with hyper-laplacian loss and data-driven outlier detection Type de document : Article/Communication Auteurs : Zeyang Dou, Auteur ; Kun Gao, Auteur ; Xiaodian Zhang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 6550 - 6564 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] distribution de Gauss
[Termes IGN] erreur
[Termes IGN] image hyperspectrale
[Termes IGN] reconstruction d'image
[Termes IGN] valeur aberranteRésumé : (auteur) Hyperspectral unmixing, which estimates end-members and their corresponding abundance fractions simultaneously, is an important task for hyperspectral applications. In this article, we propose a new autoencoder-based hyperspectral unmixing model with three novel components. First, we propose a new sparse prior to abundance maps. The proposed prior, called orthogonal sparse prior (OSP), is based on the observations that different abundance maps are close to orthogonal because, generally, no more than two end-members are mixed within one pixel. As opposed to the conventional norm-based sparse prior that assumes the abundance maps are independent, the proposed OSP explores the orthogonality between the abundance maps. Second, we propose the hyper-Laplacian loss to model the reconstruction error. The key observation is that the reconstruction error distribution usually has a heavy-tailed shape, which is better modeled by the hyper-Laplacian distribution rather than the commonly used Gaussian distribution. Third, to ease the side effect of outliers for end-member initializations, we develop a data-driven approach to detect outliers from the raw hyperspectral images. Extensive experiments on both synthetic and real-world data sets show that the proposed method significantly and consistently outperforms the compared state-of-the-art methods, with up to more than 50% improvements. Numéro de notice : A2020-532 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2977819 Date de publication en ligne : 16/03/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2977819 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95715
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 9 (September 2020) . - pp 6550 - 6564[article]How do species and data characteristics affect species distribution models and when to use environmental filtering? / Lukáš Gábor in International journal of geographical information science IJGIS, vol 34 n° 8 (August 2020)
[article]
Titre : How do species and data characteristics affect species distribution models and when to use environmental filtering? Type de document : Article/Communication Auteurs : Lukáš Gábor, Auteur ; Vítězslav Moudrý, Auteur ; Vojtěch Barták, Auteur ; Vincent Lecours, Auteur Année de publication : 2020 Article en page(s) : pp 1567 - 1584 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] distribution spatiale
[Termes IGN] données environnementales
[Termes IGN] données localisées
[Termes IGN] échantillonnage (statistique)
[Termes IGN] entropie maximale
[Termes IGN] erreur d'échantillon
[Termes IGN] filtrage d'information
[Termes IGN] interaction spatialeRésumé : (auteur) Species distribution models (SDMs) are widely used in ecology and conservation. However, their performance is known to be affected by a variety of factors related to species occurrence characteristics. In this study, we used a virtual species approach to overcome the difficulties associated with testing of combined effects of those factors on performance of presence-only SDMs when using real data. We focused on the individual and combined roles of factors related to response variable (i.e. sample size, sampling bias, environmental filtering, species prevalence, and species response to environmental gradients). Results suggest that environmental filtering is not necessarily helpful and should not be performed blindly, without evidence of bias in species occurrences. The more gradual the species response to environmental gradients is, the greater is the model sensitivity to an inappropriate use of environmental filtering, although this sensitivity decreases with higher species prevalence. Results show that SDMs are affected to the greatest degree by the species response to environmental gradients, species prevalence, and sample size. Models’ accuracy decreased with sample size below 300 presences. Furthermore, a high level of interactions among individual factors was observed. Ignoring the combined effects of factors may lead to misleading outcomes and conclusions. Numéro de notice : A2020-414 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1615070 Date de publication en ligne : 14/05/2019 En ligne : https://doi.org/10.1080/13658816.2019.1615070 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95465
in International journal of geographical information science IJGIS > vol 34 n° 8 (August 2020) . - pp 1567 - 1584[article]A comprehensive framework for studying diffusion patterns of imported dengue with individual-based movement data / Haiyan Tao in International journal of geographical information science IJGIS, vol 34 n° 3 (March 2020)PermalinkLandslide susceptibility mapping using maximum entropy and support vector machine models along the highway corridor, Garhwal Himalaya / Vijendra Kumar Pandey in Geocarto international, vol 35 n° 2 ([01/02/2020])PermalinkApplication de la loi de Benford au contrôle de qualité des modèles numériques de terrain / Laurent Polidori in XYZ, n° 158 (mars 2019)PermalinkPermalinkSignaux et systèmes / André Quinquis (2019)PermalinkCAVIAR: an R package for checking, displaying and processing wood-formation-monitoring data / Cyrille B.K. Rathgeber in Tree Physiology, vol 38 n° 8 (August 2018)PermalinkCombining land cover products using a minimum divergence and a Bayesian data fusion approach / Sarah Gengler in International journal of geographical information science IJGIS, vol 32 n° 3-4 (March - April 2018)PermalinkPermalinkDecomposition of LiDAR waveforms by B-spline-based modeling / Xiang Shen in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)PermalinkDevelopment and Comparison of Species Distribution Models for Forest Inventories / Óscar Rodríguez de Rivera in ISPRS International journal of geo-information, vol 6 n° 6 (June 2017)Permalink