Efficient Collection of Connected Vehicle Data based on Compressive Sensing*
暂无分享,去创建一个
[1] David L Donoho,et al. Compressed sensing , 2006, IEEE Transactions on Information Theory.
[2] Zhenhua Zhang,et al. Abnormal Spatial-Temporal Pattern Analysis for Niagara Frontier Border Wait Times , 2017, ArXiv.
[3] R.G. Baraniuk,et al. Compressive Sensing [Lecture Notes] , 2007, IEEE Signal Processing Magazine.
[4] Emmanuel J. Candès,et al. Robust uncertainty principles: exact signal reconstruction from highly incomplete frequency information , 2004, IEEE Transactions on Information Theory.
[5] Simon A. Dobson,et al. Energy-Efficient Sensing in Wireless Sensor Networks Using Compressed Sensing , 2014, Sensors.
[6] Lei Zhu,et al. Bi-National Delay Pattern Analysis For Commercial and Passenger Vehicles at Niagara Frontier Border , 2017, ArXiv.
[7] Adel W. Sadek,et al. Quantifying uncertainty in short-term traffic prediction and its application to optimal staffing plan development , 2018, Transportation Research Part C: Emerging Technologies.
[8] Karl Wunderlich. Dynamic Interrogative Data Capture (DIDC) Concept of Operations , 2016 .
[9] W. Bajwa,et al. A restricted isometry property for structurally-subsampled unitary matrices , 2009, 2009 47th Annual Allerton Conference on Communication, Control, and Computing (Allerton).
[10] Lin Lei. Fuzzy Control Modeling and Simulation for Urban Traffic Lights at Single Intersection , 2009 .
[11] S. S. Ravi,et al. Compression of trajectory data: a comprehensive evaluation and new approach , 2014, GeoInformatica.
[12] Milos Hauskrecht,et al. A Supervised Time Series Feature Extraction Technique Using DCT and DWT , 2009, 2009 International Conference on Machine Learning and Applications.
[13] Adel W. Sadek,et al. A Novel Variable Selection Method based on Frequent Pattern Tree for Real-time Traffic Accident Risk Prediction , 2015, ArXiv.
[14] Aziza I. Hussein,et al. Compressive Sensing Algorithms for Signal Processing Applications: A Survey , 2015 .
[15] Lei Lin,et al. A combined M5P tree and hazard-based duration model for predicting urban freeway traffic accident durations. , 2016, Accident; analysis and prevention.
[16] Shuang Cong,et al. State of the art and prospects of structured sensing matrices in compressed sensing , 2015, Frontiers of Computer Science.
[17] Emmanuel J. Candès,et al. Near-Optimal Signal Recovery From Random Projections: Universal Encoding Strategies? , 2004, IEEE Transactions on Information Theory.