THIS DESIGN IS PROVIDED TO YOU "AS IS". XILINX MAKES AND YOU RECEIVE NO WARRANTIES OR CONDITIONS, EXPRESS, IMPLIED, STATUTORY OR OTHERWISE, AND XILINX SPECIFICALLY DISCLAIMS ANY IMPLIED WARRANTIES OF MERCHANTABILITY, NON-INFRINGEMENT, OR FITNESS FOR A PARTICULAR PURPOSE. This design has not been verified on hardware (as opposed to simulations), and it should be used only as an example design, not as a fully functional core. XILINX does not warrant the performance, functionality, or operation of this Design will meet your requirements, or that the operation of the Design will be uninterrupted or error free, or that defects in the Design will be corrected. Furthermore, XILINX does not warrant or make any representations regarding use or the results of the use of the Design in terms of correctness, accuracy, reliability or otherwise.
標簽： CONDITIONS WARRANTIES YOU PROVIDED
上傳時間： 2016-03-21
上傳用戶：1427796291
法國cromda編寫的新版本MATRICE 2（矩陣和矢量運算單元）。 // ---------------------------------------------------------- // 12-01-02 : MODIFIED Matrice to Matrice2 (Delphi 6) // All routines now operate on rectangular matrix, except (InvMat and SysLin) // No more need to use the InitMat procedure (suppressed) : // - the routines detect automaticaly the dimensions of matrix and vector // - error code MatDimNul is generated if zero lines or column in matrix and vector (See DimensionMatrice and DimensionVecteur) // - error code MatMauvDim is generated if the dimensions of matrix/vector don t allow valid result // - // The result matrix is dimensioned automaticaly
上傳時間： 2014-01-23
上傳用戶：sy_jiadeyi
Just what is a regular expression, anyway? Take the tutorial to get the long answer. The short answer is that a regular expression is a compact way of describing complex patterns in texts. You can use them to search for patterns and, once found, to modify the patterns in complex ways. You can also use them to launch programmatic actions that depend on patterns. A tongue-in-cheek comment by programmers is worth thinking about: "Sometimes you have a programming problem and it seems like the best solution is to use regular expressions now you have two problems." Regular expressions are amazingly powerful and deeply expressive. That is the very reason writing them is just as error-prone as writing any other complex programming code. It is always better to solve a genuinely simple problem in a simple way when you go beyond simple, think about regular expressions. Tutorial: Using regular expressions
標簽： expression the tutorial regular
上傳時間： 2013-12-19
上傳用戶：sardinescn
（五）測試數據：n=0 n=-1 n=2 a 1 2 a 2 3 a 3 4 d 3 5 n=2 a 1 5 a 2 10 d 1 15 a 3 20 a 4 25 a 5 30 d 2 35 d 4 40 e 0 0 （六）測試結果：error error 沒付錢，沒停就走了 第一輛車付50元 第二輛車付125元 第三輛車沒出來 第四輛車付25元 第五輛車沒進入
上傳時間： 2014-02-08
上傳用戶：wfeel
The jacobi.f program solves the Helmholtz equation on a regular mesh, using an iterative Jacobi method with over-relaxation. Parallelism is exploited in both the solver and the numerical error checking
標簽： Helmholtz iterative equation program
上傳時間： 2016-04-03
上傳用戶：杜瑩12345
測試光纖通信誤碼率 采用串口RS232接口，與下位機相連，中間通過光纖傳輸，光電轉換來測試光纖通信誤碼率 VC6.0編譯通過-fiber code error testing
上傳時間： 2016-04-04
上傳用戶：wangchong
A digital fi‘equeney meter designed with FPGA development software Q-~us 11 is introduced．The 1 Hz—l MHz input measured pulse signals of the digital ii‘equency meter can be used for measuring frequency，period，pulse width and duty ratio，etc．The test results stably display O71 3 seven—segment numeric tubes，and the measuring ranges may be switched over automatically．The measuring error is equal to or less than 0．1％．
標簽： development introduced designed software
上傳時間： 2016-04-09
上傳用戶：stewart·
In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: Nando de Freitas, Mahesan Niranjan and Andrew Gee Nonlinear State Space Estimation with Neural Networks and the EM algorithm After downloading the file, type "tar -xf EMdemo.tar" to uncompress it. This creates the directory EMdemo containing the required m files. Go to this directory, load matlab5 and type "EMtremor". The figures will then show you the simulation results, including ROC curves, likelihood plots, decision boundaries with error bars, etc. WARNING: Do make sure that you monitor the log-likelihood and check that it is increasing. Due to numerical errors, it might show glitches for some data sets.
標簽： Rauch-Tung-Striebel algorithm smoother which
上傳時間： 2016-04-15
上傳用戶：zhenyushaw
基于BP神經網絡的 參數自學習控制 （1）確定BP網絡的結構，即確定輸入層節點數M和隱含層節點數Q，并給出各層加權系數的初值 和 ，選定學習速率 和慣性系數 ，此時k=1； （2）采樣得到rin(k)和yout(k)，計算該時刻誤差error(k)=rin(k)-yout(k)； （3）計算神經網絡NN各層神經元的輸入、輸出，NN輸出層的輸出即為PID控制器的三個可調參數 ， ， ； （4）根據(3.34)計算PID控制器的輸出u(k)； （5）進行神經網絡學習，在線調整加權系數 和 ，實現PID控制參數的自適應調整； （6）置k=k+1，返回（1）。
上傳時間： 2016-04-26
上傳用戶：無聊來刷下
runs Kalman-Bucy filter over observations matrix Z for 1-step prediction onto matrix X (X can = Z) with model order p V = initial covariance of observation sequence noise returns model parameter estimation sequence A, sequence of predicted outcomes y_pred and error matrix Ey (reshaped) for y and Ea for a along with inovation prob P = P(y_t | D_t-1) = evidence
標簽： matrix observations Kalman-Bucy prediction
上傳時間： 2016-04-28
上傳用戶：huannan88
