The #1 Step-by-Step Guide to labviewNow Completely Updated for labview 8! Master labview 8 with the industry's friendliest, most intuitive tutorial: labview for Everyone, Third Edition. Top labview experts Jeffrey Travis and Jim Kring teach labview the easy way: through carefully explained, step-by-step examples that give you reusable code for your own projects! This brand-new Third Edition has been fully revamped and expanded to reflect new features and techniques introduced in labview 8. You'll find two new chapters, plus dozens of new topics, including Project Explorer, AutoTool, XML, event-driven programming, error handling, regular expressions, polymorphic VIs, timed structures, advanced reporting, and much more. Certified labview Developer (CLD) candidates will find callouts linking to key objectives on NI's newest exam, making this book a more valuable study tool than ever. Not just what to d why to do it! Use labview to build your own virtual workbench Master labview's foundations: wiring, creating, editing, and debugging VIs; using controls and indicators; working with data structures; and much more Learn the "art" and best practices of effective labview development NEW: Streamline development with labview Express VIs NEW: Acquire data with NI-DAQmx and the labview DAQmx VIs NEW: Discover design patterns for error handling, control structures, state MACHINES, queued messaging, and more NEW: Create sophisticated user interfaces with tree and tab controls, drag and drop, subpanels, and more Whatever your application, whatever your role, whether you've used labview or not, labview for Everyone, Third Edition is the fastest, easiest way to get the results you're after!
上傳時間： 2013-10-14
上傳用戶：shawvi
ARM（Advanced RISC MACHINES）是微處理器行業的一家知名企業，設計了大量高性能、廉價、耗能低的RISC處理器、相關技術及軟件。技術具有性能高、成本低和能耗省的特點。適用于多種領域，比如嵌入控制、消費/教育類多媒體、DSP和移動式應用等。 ARM將其技術授權給世界上許多著名的半導體、軟件和OEM廠商，每個廠商得到的都是一套獨一無二的ARM相關技術及服務。利用這種合伙關系，ARM很快成為許多全球性RISC標準的締造者。
上傳時間： 2013-11-19
上傳用戶：偷心的海盜
核磁共振(NMR)是重要的檢測手段和分析手段之一。隨著其應用領域的拓展和 深入，核磁共振譜儀技術也不斷地發展和完善。常規商業化譜儀雖然功能強大，但 是譜儀結構復雜，體積龐大，價格昂貴，因此限制了NMR技術的應用場合。而在許 多應用場合，比如教學中，往往需要一種結構簡單，體積小巧，價格便宜，集成度 高的一體化核磁共振譜儀。 而隨著A跚(Advanced RISC MACHINES)技術的發展與成熟，本文提出了一種用 于磁共振成像系統的，基于A剛的一體化核磁共振成像譜儀的設計方案。提供了譜 儀各部分的實際性能測試的結果和譜儀整體工作的成像實驗結果，并對研制和實驗 結果進行了討論。 本論文主要內容如下： 第一，主要介紹了核磁共振原理，核磁共振成像的原理，核磁共振成像系統的結構。 第二，介紹ARM的概念與基本原理并簡要介紹了相關的軟件。 第三，介紹了一體化譜儀的研制過程，并分別從母板和核心板兩部分的硬件部分設 計與軟件部分設計上進行了相應的描述。 第四，介紹本譜儀系統的性能測試結果，并總結調試心得與現有問題，并對以后提出展望。 有關核磁共振更多知識請查看：醫學影像設備
上傳時間： 2013-11-06
上傳用戶：hanwudadi
This white paper discusses how market trends, the need for increased productivity, and new legislation have accelerated the use of safety systems in industrial machinery. This TÜV-qualified FPGA design methodology is changing the paradigms of safety designs and will greatly reduce development effort, system complexity, and time to market. This allows FPGA users to design their own customized safety controllers and provides a significant competitive advantage over traditional microcontroller or ASIC-based designs. Introduction The basic motivation of deploying functional safety systems is to ensure safe operation as well as safe behavior in cases of failure. Examples of functional safety systems include train brakes, proximity sensors for hazardous areas around MACHINES such as fast-moving robots, and distributed control systems in process automation equipment such as those used in petrochemical plants. The International Electrotechnical Commission’s standard, IEC 61508: “Functional safety of electrical/electronic/programmable electronic safety-related systems,” is understood as the standard for designing safety systems for electrical, electronic, and programmable electronic (E/E/PE) equipment. This standard was developed in the mid-1980s and has been revised several times to cover the technical advances in various industries. In addition, derivative standards have been developed for specific markets and applications that prescribe the particular requirements on functional safety systems in these industry applications. Example applications include process automation (IEC 61511), machine automation (IEC 62061), transportation (railway EN 50128), medical (IEC 62304), automotive (ISO 26262), power generation, distribution, and transportation. 圖Figure 1. Local Safety System
上傳時間： 2013-11-14
上傳用戶：zoudejile
This Application Note covers the basics of how to use Verilog as applied to ComplexProgrammable Logic Devices. Various combinational logic circuit examples, such asmultiplexers, decoders, encoders, comparators and adders are provided. Synchronous logiccircuit examples, such as counters and state MACHINES are also provided.
上傳時間： 2013-11-11
上傳用戶：y13567890
One of the strengths of Synplify is the Finite State Machine compiler. This is a powerfulfeature that not only has the ability to automatically detect state MACHINES in the sourcecode, and implement them with either sequential, gray, or one-hot encoding. But alsoperform a reachability analysis to determine all the states that could possibly bereached, and optimize away all states and transition logic that can not be reached.Thus, producing a highly optimal final implementation of the state machine.
標簽： Synplicity Machine Verilog Design
上傳時間： 2013-10-20
上傳用戶：蒼山觀海
A windows BMP file is a common image format that Java does not handle. While BMP images are used only on windows MACHINES, they are reasonably common. Reading these shows how to read complex structures in Java and how to alter they byte order from the big endian order used by Java to the little endian order used by the windows and the intel processor.
上傳時間： 2013-12-27
上傳用戶：gaojiao1999
Rainbow is a C program that performs document classification usingone of several different methods, including naive Bayes, TFIDF/Rocchio,K-nearest neighbor, Maximum Entropy, Support Vector MACHINES, Fuhr sProbabilitistic Indexing, and a simple-minded form a shrinkage withnaive Bayes.
標簽： classification different document performs
上傳時間： 2015-03-03
上傳用戶：希醬大魔王
最新的支持向量機工具箱，有了它會很方便 1. Find time to write a proper list of things to do! 2. Documentation. 3. Support Vector Regression. 4. Automated model selection. REFERENCES ========== [1] V.N. Vapnik, "The Nature of Statistical Learning Theory", Springer-Verlag, New York, ISBN 0-387-94559-8, 1995. [2] J. C. Platt, "Fast training of support vector MACHINES using sequential minimal optimization", in Advances in Kernel Methods - Support Vector Learning, (Eds) B. Scholkopf, C. Burges, and A. J. Smola, MIT Press, Cambridge, Massachusetts, chapter 12, pp 185-208, 1999. [3] T. Joachims, "Estimating the Generalization Performance of a SVM Efficiently", LS-8 Report 25, Universitat Dortmund, Fachbereich Informatik, 1999.
上傳時間： 2013-12-16
上傳用戶：亞亞娟娟123
vhdl程序源代碼，包括Combinational Logic Counters Shift Registers Memory State MACHINES Registers Systems ADC and DAC Arithmetic等
上傳時間： 2013-12-26
上傳用戶：363186
