亚洲欧美第一页_禁久久精品乱码_粉嫩av一区二区三区免费野_久草精品视频

蟲蟲首頁| 資源下載| 資源專輯| 精品軟件
登錄| 注冊

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.

    標簽: Observers Control Systems in

    上傳時間: 2020-06-10

    上傳用戶: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

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

    上傳時間: 2020-06-10

    上傳用戶: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 ; , ; , ).

    標簽: Learning Deep

    上傳時間: 2020-06-10

    上傳用戶: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.

    標簽: Deep-Learning-with-PyTorch

    上傳時間: 2020-06-10

    上傳用戶: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

    標簽: Convolutional Networks Neural Guide to

    上傳時間: 2020-06-10

    上傳用戶:shancjb

  • 路斯特ServoOne手冊

    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 

    標簽: servoone

    上傳時間: 2022-06-24

    上傳用戶:kingwide

  • VIP專區(qū)-嵌入式/單片機編程源碼精選合集系列(117)

    VIP專區(qū)-嵌入式/單片機編程源碼精選合集系列(117)資源包含以下內(nèi)容:1. (1)可以實時顯示當前時間。 (2)可以用鍵盤設(shè)定多個預定打鈴時間。 (3)學有余力的同學可以增加語音提示的功能.2. 關(guān)于ARM控制鼠標運行的C程序 所用IC為LPC2132等,程序包含接收和發(fā)送數(shù)據(jù)子程序.3. 來自PhysioNet的心電分析軟件WFDB使用指南.4. 單片機接口技術(shù)實用子程序配套源代碼 內(nèi)含關(guān)于串口通信、鍵盤控制、液晶顯示等功能的源碼.5. Boot code for ADM5120 with serial console for Edimax router..6. 論文名字為:多模式自適應嵌入式實時視覺監(jiān)督。在開發(fā)智能監(jiān)控攝像機時這篇論文會對研究者又幫助。.7. bootloader源代碼.8. 匯編的雷達程序代碼.9. 這個是51的光電隔離設(shè)計。.10. nios ii在電機控制中的應用.11. CPLD控制的數(shù)據(jù)采集器原理圖.12. 關(guān)于三星的s3c2410芯片的開發(fā)板的原理圖.13. 本程序段為mifare one 卡讀寫程序的子程序 也是關(guān)鍵程序.14. AT89C2051的設(shè)計手冊。.15. 這個是有關(guān)DS12887的資料,超級詳細的..解釋的很明白.16. s3c44b0 bios起動源程序.17. 一個Megaco實現(xiàn)源代碼.18. FPGA的Nios配合時如何計算SDRAM相位的文章.19. This an exercise in using finite state Machines.基于ALTERA的DE2開發(fā) 平臺.20. 嵌入式微處理器系統(tǒng) 崔光佐 普適計算與應用實驗室 北京大學現(xiàn)代教育技術(shù)中心 www.uclab.org.21. SST39VF160操作子程序.22. 基于51單片機的單工呼叫系統(tǒng)詳細源代碼程序.23. AT91RM9200測試程序.24. TGLCMLIMIT64A接口程序(模擬方式).25. Version Management with CVS.26.  PSoC(可編程片上系統(tǒng))是Cypress半導體公司生產(chǎn)的包含有8位微處理器核和數(shù)字與模擬混合的信號陣列芯片.27. 你相學會CPLD,FPGA,教程,快速,么,你想使用硬件編程語言么.那就看這個吧,只要5分鐘.讓你入門.28. S3C2410下LCD驅(qū)動程序移植 及GUI程序編寫 以一個實例來敘述S3C2410下一個驅(qū)動程序的編寫(本文的初始化源碼以華恒公司提供的s3c2410fb.c為基礎(chǔ))及簡單的GUI程序的編寫。.29. s3c44b0 的開發(fā)板測試的所有源代碼及程序!!!匯編代碼主要完成系統(tǒng)初始化.30. 周立功實驗串口調(diào)試! 周立功實驗串口調(diào)試!.31. 周立功實驗SPI調(diào)試! 周立功實驗SPI調(diào)試!.32. 周立功實驗SSP調(diào)試! 周立功實驗SSP調(diào)試!.33. 周立功實驗定時器調(diào)試! 周立功實驗定時器調(diào)試!.34. 周立功實驗PWM調(diào)試! 周立功實驗PWM調(diào)試!.35. PT0611打印機代碼,可用于學習用,如果有需要可以下載.36. Cyclone1C20的Nios開發(fā)板完整原理圖Protel格式.37. 尋跡小車主控程序.38. 語言嵌入式系統(tǒng)編程修煉之道,非常有用的嵌入式開發(fā)語言學習.39. 附件為at91sam9261dk評估板原理圖,protel99se格式的.40. 51單片機ADS7846適合用在4線制觸摸屏.

    標簽: 4421 FSK ISM IA

    上傳時間: 2013-06-01

    上傳用戶:eeworm

主站蜘蛛池模板: 嘉祥县| 平原县| 长兴县| 常宁市| 香河县| 延庆县| 彭阳县| 大理市| 芜湖市| 大理市| 天峻县| 尉犁县| 阳城县| 虎林市| 茶陵县| 资兴市| 松原市| 芜湖市| 江山市| 亳州市| 北辰区| 霍州市| 海兴县| 门头沟区| 秭归县| 明光市| 达孜县| 定兴县| 安丘市| 浦东新区| 拜泉县| 泸定县| 饶阳县| 香港| 朝阳市| 德江县| 博野县| 筠连县| 察雅县| 塔河县| 长治市|