The Open Radar Data Acquisition (ORDA) subsystem replaces the current WSR-88D Radar Data Acquisition subsystem with improved receiver and signal processing hardware and with improved user interface, signal processing and diagnostics software. This paper will discuss the input data from the digital receiver, the ORDA signal processing, and the data output from the ORDA hardware. Specifications of the ORDA digital receiver will be presented. The paper outlines the critical radar signal processing flow and provides analysis of new spectrum width Computations and clutter filtering schemes used in the ORDA system. Where appropriate, ORDA performance enhancements, data quality improvements and reliability and maintenance improvements will be highlighted.
标签： Radar Data Acquisition Acquisiti
上传时间： 2017-08-25
上传用户：leixinzhuo
Although state of the art in many typical machine learning tasks, deep learning algorithmsareverycostly interms ofenergyconsumption,duetotheirlargeamount of required Computations and huge model sizes. Because of this, deep learning applications on battery-constrained wearables have only been possible through wireless connections with a resourceful cloud. This setup has several drawbacks. First, there are privacy concerns. Cloud computing requires users to share their raw data—images, video, locations, speech—with a remote system. Most users are not willing to do this. Second, the cloud-setup requires users to be connected all the time, which is unfeasible given current cellular coverage. Furthermore, real-time applications require low latency connections, which cannot be guaranteed using the current communication infrastructure. Finally, wireless connections are very inefficient—requiringtoo much energyper transferredbit for real-time data transfer on energy-constrained platforms.
标签： Embedded_Deep_Learning Algorithms
上传时间： 2020-06-10
上传用户：shancjb
The 9th International Conference on Large-Scale Scientific Computations (LSSC 2013) was held in Sozopol, Bulgaria, during June 3–7, 2013. The conference was organized and sponsored by the Institute of Information and Communication Technologies at the Bulgarian Academy of Sciences.
标签： Large-Scale Scientific Computing
上传时间： 2020-06-10
上传用户：shancjb
