Algebraic Approach to Data Processing

Techniques and Applications de

,

Éditeur :

Springer


Collection :

Studies in Big Data

Paru le : 2022-10-15

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Description

The book explores a new general approach to selecting—and designing—data processing techniques. Symmetry and invariance ideas behind this algebraic approach have been successful in physics, where many new theories are formulated in symmetry terms.
The book explains this approach and expands it to new application areas ranging from engineering, medicine, education to social sciences. In many cases, this approach leads to optimal techniques and optimal solutions.
That the same data processing techniques help us better analyze wooden structures, lung dysfunctions, and deep learning algorithms is a good indication that these techniques can be used in many other applications as well.
The book is recommended to researchers and practitioners who need to select a data processing technique—or who want to design a new technique when the existing techniques do not work. It is also recommended to students who want to learn the state-of-the-art data processing.
 

Pages
250 pages
Collection
Studies in Big Data
Parution
2022-10-15
Marque
Springer
EAN papier
9783031167799
EAN PDF
9783031167805

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
25
Taille du fichier
3226 Ko
Prix
105,49 €
EAN EPUB
9783031167805

Informations sur l'ebook
Nombre pages copiables
2
Nombre pages imprimables
25
Taille du fichier
8428 Ko
Prix
105,49 €