收文单位：左列各单位 发文字号： MT-8-2-0037
上传时间： 2013-10-28
上传用户：ming529
This application note provides users with a general understanding of the SVF and XSVF fileformats as they apply to Xilinx devices. Some familiarity with IEEE STD 1149.1 (JTAG) isassumed. For information on using Serial Vector Format (SVF) and Xilinx Serial Vector Format(XSVF) files in embedded programming applications
上传时间： 2015-01-02
上传用户：时代将军
This application note shows how to achieve low-cost, efficient serial configuration for Spartan FPGA designs. The approachrecommended here takes advantage of unused resources in a design, thereby reducing the cost, part count, memory size,and board space associated with the serial configuration circuitry. As a result, neither processor nor PROM needs to be fullydedicated to performing Spartan configuration.In particular, information is provided on how the idle processing time of an on-board controller can be used to loadconfiguration data from an off-board source. As a result, it is possible to upgrade a Spartan design in the field by sending thebitstream over a network.
上传时间： 2013-11-01
上传用户：wojiaohs
MP3 portable players are the trend in music-listening technology. These players do not includeany mechanical movements, thereby making them ideal for listening to music during any type ofactivity. MP3 is a digital compression technique based on MPEG Layer 3 which stores music ina lot less space than current CD technology. Software is readily available to create MP3 filesfrom an existing CD, and the user can then download these files into a portable MP3 player tobe enjoyed in almost any environment.
上传时间： 2013-11-23
上传用户：nanxia
enter——选取或启动 esc——放弃或取消 f1——启动在线帮助窗口 tab——启动浮动图件的属性窗口 pgup——放大窗口显示比例 pgdn——缩小窗口显示比例 end——刷新屏幕 del——删除点取的元件（1个） ctrl+del——删除选取的元件（2个或2个以上） x+a——取消所有被选取图件的选取状态 x——将浮动图件左右翻转 y——将浮动图件上下翻转 space——将浮动图件旋转90度 crtl+ins——将选取图件复制到编辑区里 shift+ins——将剪贴板里的图件贴到编辑区里 shift+del——将选取图件剪切放入剪贴板里 alt+backspace——恢复前一次的操作 ctrl+backspace——取消前一次的恢复 crtl+g——跳转到指定的位置 crtl+f——寻找指定的文字
上传时间： 2013-11-01
上传用户：a296386173
为了提高直接转矩控制（DTC）系统定子磁链估计精度，降低电流、电压测量的随机误差，提出了一种基于扩展卡尔曼滤波（EKF）实现异步电机转子位置和速度估计的方法。扩展卡尔曼滤波器是建立在基于旋转坐标系下由定子电流、电压、转子转速和其它电机参量所构成的电机模型上，将定子电流、定子磁链、转速和转子角位置作为状态变量，定子电压为输入变量，定子电流为输出变量，通过对磁链和转速的闭环控制提高定子磁链的估计精度，实现了异步电机的无速度传感器直接转矩控制策略，仿真结果验证了该方法的可行性,提高了直接转矩的控制性能。 Abstract: In order to improve the Direct Torque Control（DTC） system of stator flux estimation accuracy and reduce the current， voltage measurement of random error， a novel method to estimate the speed and rotor position of asynchronous motor based on extended Kalman filter was introduced. EKF was based on d-p axis motor and other motor parameters （state vector: stator current， stator flux linkage， rotor angular speed and position； input: stator voltage； output: staror current). EKF was designed for stator flux and rotor speed estimation in close-loop control. It can improve the estimated accuracy of stator flux. It is possible to estimate the speed and rotor position and implement asynchronous motor drives without position and speed sensors. The simulation results show it is efficient and improves the control performance.
上传时间： 2015-01-02
上传用户：qingdou
随着USB技术日趋成熟，USB开发者只需要关注顶层开发即可，这样虽然减少了工作量，但容易使开发者忽略USB基础理论与概念，导致的弊端在于开发者一旦遇到问题，往往不知如何解决。作者基于多年USB开发经验，针对当前很多USB开发者容易混淆的概念，进行深入浅出的剖析，针对枚举和重枚举的区别、不同启动方式的区别等问题，进行了归纳总结。本文从对比的角度分析问题，有助于开发者理清USB的工作机理。
标签： USB
上传时间： 2013-10-26
上传用户：zaocan888
C++作业，实现vector
标签：
上传时间： 2015-01-21
上传用户：亚亚娟娟123
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.
标签： classification different document performs
上传时间： 2015-03-03
上传用户：希酱大魔王
最新的支持向量机工具箱，有了它会很方便 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.
上传时间： 2013-12-16
上传用户：亚亚娟娟123
