82 pages - February 2023
ISBN papier : Non disponible
ISBN ebook : 9781915874054


Cet ouvrage est uniquement disponible en version électronique.


– Paperback:
Free delivery for any order placed directly through the ISTE Group website istegroup.com
Delivery time: approximately two weeks
Deliveries only within metropolitan France, Belgium, Switzerland and Luxembourg
Printed in color
An ebook version is provided free with every hardcopy ordered through our website
It will be sent after the order is completed
Offer not applicable to bookshops

– Ebook:
Prices reserved for private individuals
Licenses for institutions: contact us
Our ebooks are in PDF format (readable on any device)

In a stochastic environment where reality is described through samples or examples, artificial intelligence learns by penalizing weighted differential and/or integral viewpoints. The convolutional neural framework is relevant to encompass the mathematical operations performed by such an artificial intelligence. Conversely, mathematical compositions alternating convolutions and non linear operators are powerful tools for generating complex artificial realities.

This book proposes a stochastic integral perspective of deep machine learning in artificial intelligence. The organization of the book is as follows. Chapter 1 introduces the basics of stochastic reasoning and the most useful properties of stochastic processes. Chapters 2 and 3 derive stochastic convoluted models for the construction, analysis and simulation of fractionally integrated fields. Chapter 4 highlights how some deep artificial neurons can disentangle the very long-range stochastic dependencies, when these neurons are parameterized to integrate spectral responses.

(FR) 1. The Minimum You Need to Know About Stochastic Processes
2. Stochastic Discrete Domain Convolutive Integration Models
3. Stochastic Continuous Domain Convolutive Integration Models
4. On Machine Learning of Very Long-Range Spatial Dependence Structures

Abdourrahmane M. Atto

Abdourrahmane M. Atto is Associate Professor at the University Savoie Mont Blanc, France. His research interests concern mathematical methods and models for artificial intelligence and image time series.