A novel method for driving condition recognition based on Compressed Sensing

Proceedings of the ASME Design Engineering Technical Conference

Volumn 1, Issue , 2013, Pages

  Zhang, Xing ^a   Dong, Zuomin ^a   Crawford, Curran ^a  

^a UNIVERSITY OF VICTORIA   (Canada)

Author keywords

Compressed sensing; Driving condition recognition; Machine learning; Support vector machine

Indexed keywords

COMPRESSED SENSING; DESIGN; HYBRID VEHICLES; LEARNING SYSTEMS; SUPPORT VECTOR MACHINES;

ALTERNATIVE ENERGY; CLASSIFICATION ACCURACY; DRIVING ASSISTANCE SYSTEMS; DRIVING CONDITIONS; HYBRID-ELECTRIC VEHICLES; VEHICLE SPEED;

SIGNAL RECONSTRUCTION;

EID: 84896966406     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1115/DETC2013-13202     Document Type: Conference Paper

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