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portada Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems
Type
Physical Book
Publisher
Language
English
Pages
789
Format
Hardcover
Dimensions
23.4x15.6x4.3 cm
Weight
1.30 kg.
ISBN13
9783031280153

Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems

Kukkala, Vipin Kumar ; Pasricha, Sudeep (Author) · Springer · Hardcover

Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems - Kukkala, Vipin Kumar ; Pasricha, Sudeep

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Synopsis "Machine Learning and Optimization Techniques for Automotive Cyber-Physical Systems"

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.

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