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Faire une suggestion Affiner la rechercheBiosignal acquisition and processing / Hugo Humberto Placido da Silva (2024)
Titre : Biosignal acquisition and processing : a project-based learning approach Type de document : texte imprimé Auteurs : Hugo Humberto Placido da Silva (19..-..), Auteur ; Hugo Filipe Silveira Gamboa (19..-..), Auteur ; Rui Pedro Sousa Varandas (19..-..), Auteur ; Guilherme Alexandre dos Santos Espadanal Ramos (19..-..), Auteur Editeur : Cham : Springer Année de publication : 2024 Collection : Learning materials in biosciences Importance : 1 vol. (VIII-352 p.) Présentation : ill. en noir et en coul., fig., couv. ill Format : 25 cm ISBN/ISSN/EAN : 978-3-031-35186-0 Langues : Anglais (eng) Catégories : Biocapteurs ; Biosensors ; Enseignement Technical aspects of the teaching process. Use more specific descriptor where appropriate.; G?enie biom?edical ; Project method in teaching ; Signal processing ; Traitement du signalIndex. décimale : 610.28 Résumé : This textbook provides an introduction to common concepts in biosignal acquisition and processing, rooted in a Project-Based Learning (PBL). A series of exercises and corresponding solutions is described, with a focus on common problems that new entrants encounter in the undergraduate and graduate curriculums in biomedical engineering, psychophysiology, human-computer interaction, physiotherapy, and others developing work in the boundary between biosignal acquisition and other disciplines. Solutions include both hardware and software components, encompassing sensor design, biosignals acquisition using the Arduino and BITalino platforms, Python for signal processing, analysis, and knowledge extraction, including also HTML/CSS/JavaScript for user interface design. All the content is supported with rich graphics, source code, and other useful resources made available to the interested reader. This is an ideal book for undergraduate students and practitioners (across disciplines) who are studying or working in the field of biomedical signal acquisition, processing, and analysis Biosignal acquisition and processing : a project-based learning approach [texte imprimé] / Hugo Humberto Placido da Silva (19..-..), Auteur ; Hugo Filipe Silveira Gamboa (19..-..), Auteur ; Rui Pedro Sousa Varandas (19..-..), Auteur ; Guilherme Alexandre dos Santos Espadanal Ramos (19..-..), Auteur . - Cham : Springer, 2024 . - 1 vol. (VIII-352 p.) : ill. en noir et en coul., fig., couv. ill ; 25 cm. - (Learning materials in biosciences) .
ISBN : 978-3-031-35186-0
Langues : Anglais (eng)
Catégories : Biocapteurs ; Biosensors ; Enseignement Technical aspects of the teaching process. Use more specific descriptor where appropriate.; G?enie biom?edical ; Project method in teaching ; Signal processing ; Traitement du signalIndex. décimale : 610.28 Résumé : This textbook provides an introduction to common concepts in biosignal acquisition and processing, rooted in a Project-Based Learning (PBL). A series of exercises and corresponding solutions is described, with a focus on common problems that new entrants encounter in the undergraduate and graduate curriculums in biomedical engineering, psychophysiology, human-computer interaction, physiotherapy, and others developing work in the boundary between biosignal acquisition and other disciplines. Solutions include both hardware and software components, encompassing sensor design, biosignals acquisition using the Arduino and BITalino platforms, Python for signal processing, analysis, and knowledge extraction, including also HTML/CSS/JavaScript for user interface design. All the content is supported with rich graphics, source code, and other useful resources made available to the interested reader. This is an ideal book for undergraduate students and practitioners (across disciplines) who are studying or working in the field of biomedical signal acquisition, processing, and analysis Réservation
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Code-barres Cote Support Localisation Section Disponibilité 9843 610.28/SIL Livre Livres de la Bibliothèque FSNVST Sciences médicales (Généralités) Disponible Python recipes for earth sciences / Martin H Trauth (C 2022)
Titre : Python recipes for earth sciences Type de document : texte imprimé Auteurs : Martin H Trauth (1963-..), Auteur Editeur : Cham : Springer Année de publication : C 2022 Collection : Springer Textbooks in Earth Sciences, Geography and Environment, ISSN 2510-1307 Importance : 1 vol. (XII-453 p.) Présentation : ill. en coul., couv. ill. en coul Format : 24 cm ISBN/ISSN/EAN : 978-3-031-07718-0 Langues : Anglais (eng) Catégories : G?eologie ; Python (Computer program language) ; Python (langage de programmation) ; Sciences de la terre Résumé : Python is used in a wide range of geoscientific applications, such as in processing images for remote sensing, in generating and processing digital elevation models, and in analyzing time series. This book introduces methods of data analysis in the geosciences using Python that include basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, and signal processing; the analysis of spatial and directional data; and image analysis. The text includes numerous examples that demonstrate how Python can be used on data sets from the earth sciences. The supplementary electronic material (available online through Springer Link) contains the example data as well as recipes that include all the Python commands featured in the book Python recipes for earth sciences [texte imprimé] / Martin H Trauth (1963-..), Auteur . - Cham : Springer, C 2022 . - 1 vol. (XII-453 p.) : ill. en coul., couv. ill. en coul ; 24 cm. - (Springer Textbooks in Earth Sciences, Geography and Environment, ISSN 2510-1307) .
ISBN : 978-3-031-07718-0
Langues : Anglais (eng)
Catégories : G?eologie ; Python (Computer program language) ; Python (langage de programmation) ; Sciences de la terre Résumé : Python is used in a wide range of geoscientific applications, such as in processing images for remote sensing, in generating and processing digital elevation models, and in analyzing time series. This book introduces methods of data analysis in the geosciences using Python that include basic statistics for univariate, bivariate, and multivariate data sets, time series analysis, and signal processing; the analysis of spatial and directional data; and image analysis. The text includes numerous examples that demonstrate how Python can be used on data sets from the earth sciences. The supplementary electronic material (available online through Springer Link) contains the example data as well as recipes that include all the Python commands featured in the book Exemplaires(0)
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