Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Vahid Behravan"'
Publikováno v:
2017 IEEE 2nd International Conference on Signal and Image Processing (ICSIP).
In this paper we propose a mechanism for adaptive compressive-sensing of 3D point cloud. One problem with conventional compressive-sensing algorithm is a-priori fixed compression rate. In this work, we show that there is a correlation between sparsit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ddb03b987a44edd4e637a09c46411232
https://doi.org/10.1109/siprocess.2017.8124530
https://doi.org/10.1109/siprocess.2017.8124530
Publikováno v:
CIS
In this paper we propose a framework for analyzing 3D point cloud data compression using compressive-sensing. This framework uses real 3D point clouds and investigates different error sources that may affect performance of the system. Experimental re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b298415130afc3ef46680e7bd1a3b8a1
https://doi.org/10.1109/cis.2016.0024
https://doi.org/10.1109/cis.2016.0024
Autor:
Xiong Zhou, Sanfeng Zhang, Arun Natarajan, Patrick Chiang, Qiang Li, Hailiang Yao, Shuo Li, Zhiliang Hong, Vahid Behravan
Publikováno v:
2016 IEEE MTT-S International Wireless Symposium (IWS).
This paper presents a sub-nanowatt front-end amplifier for ultra-low-power wireless IoT sensor nodes. This chip consists of an instrumentation amplifier, a DC servo loop, a clock generator and a bias circuit. It is fully integrated, and therefore doe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81a46a2e28c2768b782dc71ba8c08a35
https://doi.org/10.1109/ieee-iws.2016.7585429
https://doi.org/10.1109/ieee-iws.2016.7585429
Autor:
Mateen C. Moghbel, Vahid Behravan, Dhiraj Baruah, Mijail Serruya, Glenn T. Stebbins, Fathima Fijula Palot Manzil, Madhav Thambisetty, Gaurav Jindal, Aaron S. Field, Dennis Chan, Kala Venkiteswaran, Sol De Jesus, Jitender Saini, Andrew Newberg, Ritu Shah, Sumei Wang, A.M. Barrett, Ruth A. Wood, Robert S. Stern, Inga Katharina Koerte, Vivek Prabhakaran, Elisabeth B. Lucassen, Dheeraj Gandhi, David J. Brooks, Sampson K. Kyere, Krishan K. Jain, Stefan Ropele, Marie Sarazin, Aristides A. Capizzano, Maya Lichtenstein, Suyash Mohan, Donald G. McLaren, Kenneth M. Lury, Amit K. Agarwal, Puneet S. Devgun, Sanjeev Chawla, Mark D. Meadowcroft, Alexander P. Lin, Harish Poptani, Yoshimitsu Ohgiya, Jeffrey D. Poot, Douglas V. Merkitch, Olaguoke Akinwande, Jennifer G. Goldman, Martha E. Shenton, Christian La, Guofan Xu, Rakesh K. Gupta, Kei Yamada, Gálvez-Jiménez Néstor, Marc Mühlmann, Divisha Raheja, Rashmi Tondon, Vijay K. Mittal, Zachary Simmons, Boris-Stephan Rauchmann, Koji Sakai, Nicola Pavese, Néstor Gálvez-Jiménez, Thyagarajan Subramanian, Ludovico Minati, Hazem M. Matta, Christian Langkammer, Vinod G. Maller, Abass Alavi, Surjith Vattoth, John W. Ebersole, Leslie Hartman, Maria Martinez-Lage Alvarez, Tushar Chandra, Qing X. Yang, Kyaw Nyan Tun, Sangam G. Kanekar, Brian S. Bentley, Wolfgang Gaggl, Toshio Moritani, Falgun H. Chokshi, Jeffrey Kyle Cooper, Leonardo Cruz Souza de, Girish Bathla, Dejan Samardzic, Michael Mayinger, Mauricio Castillo
Publikováno v:
Imaging of Neurodegenerative Disorders
Neurodegenerative diseases comprise a broad swath of different neurologic diseases characterized by loss of neurons in the central nervous system. The most common neurodegenerative disease is Alzheimer disease, a dementing disease. Dementia is common
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::268722ee7ced35e560a3f0f1b2ff97c7
https://doi.org/10.1055/b-003-129350
https://doi.org/10.1055/b-003-129350
Autor:
Shuo Li, Chia-Hung Chen, Mohammed Shoaib, Gabor C. Temes, Neil E. Glover, Vahid Behravan, Patrick Chiang
Publikováno v:
CICC
Reconstructing signals accurately is a critical aspect of compressed sensing. We propose a compressed-sensing sensor-on-chip that compresses and also extracts key statistics of the input signal at sampling time. These statistics can be used at the re
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::bb2fc128491ebf15fa3e71d8d4d90b59
https://doi.org/10.1109/cicc.2015.7338429
https://doi.org/10.1109/cicc.2015.7338429
Publikováno v:
BSN
Biomedical signals exhibit substantial variance in their sparsity, preventing conventional a-priori open-loop setting of the compressed sensing (CS) compression factor. In this work, we propose, analyze, and experimentally verify a rate-adaptive comp
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::7b6bd88a29983a032e710ecf8d4555df
https://doi.org/10.1109/bsn.2015.7299419
https://doi.org/10.1109/bsn.2015.7299419