%0 Conference Paper %1 conf/apsipa/SuT20 %A Su, Juyn-Da %A Tsai, Pei-Yun %B APSIPA %D 2020 %I IEEE %K dblp %P 82-87 %T Processing Element Architecture Design for Deep Reinforcement Learning with Flexible Block Floating Point Exploiting Signal Statistics. %U http://dblp.uni-trier.de/db/conf/apsipa/apsipa2020.html#SuT20 %@ 978-988-14768-8-3

@inproceedings{conf/apsipa/SuT20, added-at = {2021-02-11T00:00:00.000+0100}, author = {Su, Juyn-Da and Tsai, Pei-Yun}, biburl = {https://www.bibsonomy.org/bibtex/28079d723ec99843b2e34c45be5750a15/dblp}, booktitle = {APSIPA}, crossref = {conf/apsipa/2020}, ee = {https://ieeexplore.ieee.org/document/9306500}, interhash = {8af374136d8cb3f3ed3daab9865a3871}, intrahash = {8079d723ec99843b2e34c45be5750a15}, isbn = {978-988-14768-8-3}, keywords = {dblp}, pages = {82-87}, publisher = {IEEE}, timestamp = {2024-04-09T11:42:12.000+0200}, title = {Processing Element Architecture Design for Deep Reinforcement Learning with Flexible Block Floating Point Exploiting Signal Statistics.}, url = {http://dblp.uni-trier.de/db/conf/apsipa/apsipa2020.html#SuT20}, year = 2020 }