Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems

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  • Springer

  • Date de publication : 2023-09-01


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Détails du livre

Titre : Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems
Pages : 789
Collection : n.c
Parution : 2023-09-01
Éditeur : Springer
EAN papier : 9783031280153
À propos du livre


This book provides comprehensive coverage of various solutions that address issues related to real-time performance, security, and robustness in emerging automotive platforms. The authors discuss recent advances towards the goal of enabling reliable, secure, and robust, time-critical automotive cyber-physical systems, using advanced optimization and machine learning techniques. The focus is on presenting state-of-the-art solutions to various challenges including real-time data scheduling, secure communication within and outside the vehicle, tolerance to faults, optimizing the use of resource-constrained automotive ECUs, intrusion detection, and developing robust perception and control techniques for increasingly autonomous vehicles.

Format EPUB - Nb pages copiables : 7 - Nb pages imprimables : 78 - Poids : 100854 Ko - - Prix : 117,69 € - EAN : 9783031280160

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