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上传时间： 2019-12-02
上传用户：hjd0303
针对永磁同步电机多个参数同时辨识时会出现欠秩的情况， 介绍了在 dq 坐标系下采用最小二乘法将多个参数分开辨识的方法。在硬件在环平台上采用该方法对电阻、电感和磁链进行了辨识。最后进一步考虑到电阻和磁链受温度的影响大， 进行了考虑温升的电阻和磁链的辨识。经验证， 该方法可以比较准确地辨识出电机参数。
上传时间： 2019-12-05
上传用户：ni952777
在生活日益丰富， 活动多种多样的今天， 人们在参加各项活动的同时不可避免的遇到活 动的考勤与签到。传统的签到采用点名或自行签名的方式有着耗时、代签、难以统计等弊端。 而如今， 随着互联网的普及以及有着人工智能加持的服务， 我们的签到系统也可以跟上时代 发展的步伐。 智能手机的普及， 微信已成为大家装机必备的软件之一， 深深地影响着人们的 生活习惯。而近年来火爆的微信小程序，借助微信这个平台，凭借自身免下载、功能多样、 体积小等特点日益流行。因此，借助微信小程序开发的考勤签到系统能够满足活动的发起者、 活动的参与者的需求。
上传时间： 2020-02-27
上传用户：zqszqs
fds 选择文件 X 飞行器半实物仿真初案_
上传时间： 2020-03-06
上传用户：stormfree
In order to improve the spectral efficiency in wireless communications, multiple antennas are employed at both transmitter and receiver sides, where the resulting system is referred to as the multiple-input multiple-output (MIMO) system. In MIMO systems, it is usually requiredto detect signals jointly as multiple signals are transmitted through multiple signal paths between the transmitter and the receiver. This joint detection becomes the MIMO detection.
标签： Complexity Detection MIMO Low
上传时间： 2020-05-27
上传用户：shancjb
Many applications have required the positioning accuracy of a Global Navigation Satellite System (GNSS). Some applications exist in environments that attenuate GNSS signals, and, consequently, the received GNSS signals become very weak. Examplesofsuchapplicationsarewirelessdevicepositioning,positioninginsensor networks that detect natural disasters, and orbit determination of geostationary and high earth orbit (HEO) satellites. Conventional GNSS receivers are not designed to work with weak signals. This book presents novel GNSS receiver algorithms that are designed to work with very weak signals.
标签： Receivers Signals GNSS Weak for
上传时间： 2020-06-09
上传用户：shancjb
The past decade has seen an explosion of machine learning research and appli- cations; especially, deep learning methods have enabled key advances in many applicationdomains,suchas computervision,speechprocessing,andgameplaying. However, the performance of many machine learning methods is very sensitive to a plethora of design decisions, which constitutes a considerable barrier for new users. This is particularly true in the booming field of deep learning, where human engineers need to select the right neural architectures, training procedures, regularization methods, and hyperparameters of all of these components in order to make their networks do what they are supposed to do with sufficient performance. This process has to be repeated for every application. Even experts are often left with tedious episodes of trial and error until they identify a good set of choices for a particular dataset.
标签： Auto-Machine-Learning-Methods-Sys tems-Challenges
上传时间： 2020-06-10
上传用户：shancjb
This manuscript is a partial draft of a book to be published in early 1994 by AddisonWesley (ISBN 0-201-63337-X). Addison-Wesley has given me permission to make drafts of the book available to the Tcl community to help meet the need for introductory documentation on Tcl and Tk until the book becomes available. Please observe the restrictions set forth in the copyright notice above: you’re welcome to make a copy for yourself or a friend but any sort of large-scale reproduction or reproduction for profit requires advance permission from Addison-Wesley
标签： Toolkit
上传时间： 2020-07-05
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本文档对无刷直流 (BLDC) 电机的使用进行了说明。 虽然可将无刷特点应用 于几种类型的电机（交流同步电机、 步进电机、 开关磁阻电机和交流感应电机） ， BLDC 具有梯形反电动势和（120 电角宽度） 矩形定子电流 的永磁同步机器被广泛使用， 其次， 无刷直流驱动器显示出极高的机械功率密度。这份应用报告涵盖了 280x 控制器和从 BLDC 电机驱动中获得高性能的某些系统注意事项。
上传时间： 2020-10-21
上传用户：
选择文件 X 双色球彩票过滤器 绿色免费版
上传时间： 2020-11-27
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