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MACHINES

  • Observers in Control Systems

    Control systems are used to regulate an enormous variety of MACHINES, products, and processes. They control quantities such as motion, temperature, heat flow, fluid flow, fluid pressure, tension, voltage, and current. Most concepts in control theory are based on having sensors to measure the quantity under control. In fact, control theory is often taught assuming the availability of near-perfect feedback signals. Unfortunately, such an assumption is often invalid. Physical sensors have shortcomings that can degrade a control system.

    标签: Observers Control Systems in

    上传时间: 2020-06-10

    上传用户:shancjb

  • AI-and-Robotics-IBA-GEI-April-2017

    Modern information technologies and the advent of MACHINES powered by artificial intelligence (AI) have already strongly influenced the world of work in the 21st century. Computers, algorithms and software simplify everyday tasks, and it is impossible to imagine how most of our life could be managed without them. However, is it also impossible to imagine how most process steps could be managed without human force? The information economy characterised by exponential growth replaces the mass production industry based on economy of scales

    标签: AI-and-Robotics-IBA-GEI-April 2017

    上传时间: 2020-06-10

    上传用户:shancjb

  • Deep Learning---1

    Inventors have long dreamed of creating MACHINES that think. This desire dates back to at least the time of ancient Greece. The mythical figures Pygmalion, Daedalus, and Hephaestus may all be interpreted as legendary inventors, and Galatea, Talos, and Pandora may all be regarded as artificial life ( , Ovid and Martin 2004 Sparkes 1996 Tandy 1997 ; , ; , ).

    标签: Learning Deep

    上传时间: 2020-06-10

    上传用户:shancjb

  • Deep-Learning-with-PyTorch

    We’re living through exciting times. The landscape of what computers can do is changing by the week. Tasks that only a few years ago were thought to require higher cognition are getting solved by MACHINES at near-superhuman levels of per- formance. Tasks such as describing a photographic image with a sentence in idiom- atic English, playing complex strategy game, and diagnosing a tumor from a radiological scan are all approachable now by a computer. Even more impressively, computers acquire the ability to solve such tasks through examples, rather than human-encoded of handcrafted rules.

    标签: Deep-Learning-with-PyTorch

    上传时间: 2020-06-10

    上传用户:shancjb

  • Guide to Convolutional Neural Networks

    General paradigm in solving a computer vision problem is to represent a raw image using a more informative vector called feature vector and train a classifier on top of feature vectors collected from training set. From classification perspective, there are several off-the-shelf methods such as gradient boosting, random forest and support vector MACHINES that are able to accurately model nonlinear decision boundaries. Hence, solving a computer vision problem mainly depends on the feature extraction algorithm

    标签: Convolutional Networks Neural Guide to

    上传时间: 2020-06-10

    上传用户:shancjb

  • 路斯特ServoOne手册

    German universities and scientists have repeatedly set the intermational standard in drive technology. Identification and active compensation of natural frequencies in oscillatory mechanics, status controls with monitoring structures incorporating acceleration sensors, adaptive compensation of measurement system deficiencies, self-adjusting detent torque compensation… everything invented with only a single aim in mind: to continue improv-ing the motion control, dynamics, precision and processing speed of your MACHINES. For the industrial applicabability of this technology scientific publications in proceedings and laboratory test rigs are not enough. These features consequenty need to be converted into cost-efficient and easily manageable products. That 's exactly what we have done.So in future, if you should need more than today ' smarket can offer you, now everything isgoing to be alright. With our new high-performance ServoOne drive series you will experi-ence 

    标签: servoone

    上传时间: 2022-06-24

    上传用户:kingwide

  • VIP专区-嵌入式/单片机编程源码精选合集系列(117)

    VIP专区-嵌入式/单片机编程源码精选合集系列(117)资源包含以下内容:1. (1)可以实时显示当前时间。 (2)可以用键盘设定多个预定打铃时间。 (3)学有余力的同学可以增加语音提示的功能.2. 关于ARM控制鼠标运行的C程序 所用IC为LPC2132等,程序包含接收和发送数据子程序.3. 来自PhysioNet的心电分析软件WFDB使用指南.4. 单片机接口技术实用子程序配套源代码 内含关于串口通信、键盘控制、液晶显示等功能的源码.5. Boot code for ADM5120 with serial console for Edimax router..6. 论文名字为:多模式自适应嵌入式实时视觉监督。在开发智能监控摄像机时这篇论文会对研究者又帮助。.7. bootloader源代码.8. 汇编的雷达程序代码.9. 这个是51的光电隔离设计。.10. nios ii在电机控制中的应用.11. CPLD控制的数据采集器原理图.12. 关于三星的s3c2410芯片的开发板的原理图.13. 本程序段为mifare one 卡读写程序的子程序 也是关键程序.14. AT89C2051的设计手册。.15. 这个是有关DS12887的资料,超级详细的..解释的很明白.16. s3c44b0 bios起动源程序.17. 一个Megaco实现源代码.18. FPGA的Nios配合时如何计算SDRAM相位的文章.19. This an exercise in using finite state MACHINES.基于ALTERA的DE2开发 平台.20. 嵌入式微处理器系统 崔光佐 普适计算与应用实验室 北京大学现代教育技术中心 www.uclab.org.21. SST39VF160操作子程序.22. 基于51单片机的单工呼叫系统详细源代码程序.23. AT91RM9200测试程序.24. TGLCMLIMIT64A接口程序(模拟方式).25. Version Management with CVS.26.  PSoC(可编程片上系统)是Cypress半导体公司生产的包含有8位微处理器核和数字与模拟混合的信号阵列芯片.27. 你相学会CPLD,FPGA,教程,快速,么,你想使用硬件编程语言么.那就看这个吧,只要5分钟.让你入门.28. S3C2410下LCD驱动程序移植 及GUI程序编写 以一个实例来叙述S3C2410下一个驱动程序的编写(本文的初始化源码以华恒公司提供的s3c2410fb.c为基础)及简单的GUI程序的编写。.29. s3c44b0 的开发板测试的所有源代码及程序!!!汇编代码主要完成系统初始化.30. 周立功实验串口调试! 周立功实验串口调试!.31. 周立功实验SPI调试! 周立功实验SPI调试!.32. 周立功实验SSP调试! 周立功实验SSP调试!.33. 周立功实验定时器调试! 周立功实验定时器调试!.34. 周立功实验PWM调试! 周立功实验PWM调试!.35. PT0611打印机代码,可用于学习用,如果有需要可以下载.36. Cyclone1C20的Nios开发板完整原理图Protel格式.37. 寻迹小车主控程序.38. 语言嵌入式系统编程修炼之道,非常有用的嵌入式开发语言学习.39. 附件为at91sam9261dk评估板原理图,protel99se格式的.40. 51单片机ADS7846适合用在4线制触摸屏.

    标签: 4421 FSK ISM IA

    上传时间: 2013-06-01

    上传用户:eeworm