Machine learning is a broad and fascinating field. Even today, machine learning technology runs a substantial part of your life, often without you knowing it. Any plausible approach to artifi- cial intelligence must involve learning, at some level, if for no other reason than it’s hard to call a system intelligent if it cannot learn. Machine learning is also fascinating in its own right for the philo- sophical questions it raises about what it means to learn and succeed at tasks.
标签： Learning Machine Course in
上传时间： 2020-06-10
上传用户：shancjb
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
目前电动汽车主要以锂电池作为动力来源,为了提高锂电池的使用时间和安全性,为锂电池提供安全良好的运行环境,电池管理系统应运而生。BMS主控单元基于S32K144汽车级单片机,通过主从式网络控制结构能够对锂电池的各个参数进行采集与分析。采用扩展卡尔曼滤波对电池的荷电状态(SOC)进行估算,克服普通估算方法无法避免电池内阻误差的缺点,通过Matlab/Simulink软件仿真验证可使估算误差达到2%以内。At present,electric vehicles mainly use lithium batteries as the power source.In order to improve the running time and safety of lithium batteries,a safe and good operating environment for power batteries is provided,and a battery management system(BMS) has emerged.The BMS main control unit is based on the S32K144 automotive-grade control chip.Through the master-slave network control structure,it can collect and analyze the various parameters of the lithium battery.The Extended Kalman Filter(EKF) is used to estimate the state of charge(SOC) of the battery,which overcomes the shortcomings of the internal estimation method that cannot overcome the internal resistance error of the battery.It can be verified by Matlab/Simulink software simulation.The estimation error is within 2%.
上传时间： 2022-03-26
上传用户：XuVshu
实验教学一直是工科教学中不可或缺的组成部分,对培养学生的动手能力,独立思考能力,创新思维与发散思维具有重要的作用。针对目前电路教学实验中电路仿真实验与实物电路实验各自独立,无法统一问题,提出将仿真电路实验与实物电路实验有机的结合同步操作,并使用Web发布实现远程实验操作。采用Multisim作为电路实验仿真平台,NI Eiviss II作为实物电路实验硬件平台,运用LabVIEW整合Multisim电路仿真实验与实物电路实验,实现仿真与实物实验有机结合,两种实验可同步进行。学生在仿真实验中先可探索实验,然后做实物实验。同时运用LabVIEW开发出实验过程人机交互操作接口界面,使用过程中效果良好。Experimental teaching has always been an indispensable part of engineering education.And it always plays an important role in cultivating students'practical ability,independent thinking ability,innovative thinking and divergent thinking.But simulation experiment and physical experiment cannot be unified in the circuit teaching experiment at present.In order to solve this problem,this paper proposes to combine organically the simulation circuit experiment with physical circuit experiment,and synchronously operate them.This paper uses the WEB publishing to achieve remote experimental operation.Multisim is used as the circuit simulation platform,and NI Eiviss II is used as the physical circuit hardware platform.Multisim circuit simulation experiment and physical circuit experiment are implemented by LabVIEW to realize the combination of simulation experiment and physical experiment.Students do explore experiments in simulation experiment firstly,and then do physical experiment.And this paper uses LabVIEW to develop the experimental man-machine interface.
上传时间： 2022-04-05
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