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[Windows Develop] b030717-心得三 DL : 0: 心得三——按下鼠标哪个键 1.实验目的（1）首先打开VC++6.0打开File菜单,New命令建立一个Win32 Application类型的工程,注意,在建立工程时在第2步选择\"A simple Win32 application.\".利用windows API函数进行编程的入门,编写简单的Windows应用程序,建立窗口. （2）在此基础上实现如下功能:鼠标键按下时,弹出消息框通知用户是按下了鼠标的哪个键 -experience -- which press the mouse button 1. Experiment (1) First, open the VC 6.0 Open File menu, the establishment of a New Order Win32 Application types of projects, that the establishment of projects in the first two-step selection "A simple Win32 application." . windows API function using programmed entry, to prepare a simple Windows application procedures, the establishment of the window. (2) In this on the basis of the following functions : pressing the mouse button, pop-up message box to inform the user is pressing the mouse button which
Update : 2008-10-13 Size : 37.06kb Publisher : 小钟
[Other resource] xor DL : 0: RSA算法实现(经典) 1. 　　首先要把文件夹中的rsa.c文件拷贝到运行工具（如TURBOC2）下文件夹名为INCLUDE的文件夹中。　　（在本机上已经做过，所以不需要做）　　　2. 　　RSA的加密对象为C盘下文件名为CODE.txt的前8位（如果没有一定要在C盘下建立一个文件名为CODE.txt的文件，　把要加密的数据写到文件里），加密后在C盘下生成一个文件名为RSACIPER.txt文件。　　（在本机上已经做过，所以不需要做以上二步）　　但在其它机子上一定得完成以上二步，方可运行。　3. 　　RSA的解密对象为C盘下文件名RSACIPER.txt文件，解密后在C盘下生成为End＿CODE.txt文件。运行步骤　（计算PK SK R）－－＞（A_RSA加密）－－＞（A_RSA解密）。-RSA algorithm (classic) 1. First, it is necessary folder of documents copied to rsa.c running tools (eg TURBOC2) folder called INCLUDE of folders. (In this plane has been done, so there was no need to do) 2. RSA encryption target for the C-CODE.txt document, entitled under the former eight (if not necessarily in the C - to establish a document titled CODE.txt documents, the encrypted data to document wrote), encryption in the next generation C-1 document, entitled RSACIPER.txt document. (In this plane has been done, so there was no need to do the above two-step) but on the other machine had to complete the above two steps before running. 3. RSA decryption target for the C-under File Name RSACIPER.txt documents, declassified after the C-Descent into End_CODE.txt document. Run steps (PK calc
Update : 2008-10-13 Size : 8.43kb Publisher : 杨
[Other resource] 经典rsa DL : 0: 1. 　　首先要把文件夹中的rsa.c文件拷贝到运行工具（如TURBOC2）下文件夹名为INCLUDE的文件夹中。　　（在本机上已经做过，所以不需要做）　　　2. 　　RSA的加密对象为C盘下文件名为CODE.txt的前8位（如果没有一定要在C盘下建立一个文件名为CODE.txt的文件，　把要加密的数据写到文件里），加密后在C盘下生成一个文件名为RSACIPER.txt文件。　　（在本机上已经做过，所以不需要做以上二步）　　但在其它机子上一定得完成以上二步，方可运行。　3. 　　RSA的解密对象为C盘下文件名RSACIPER.txt文件，解密后在C盘下生成为End＿CODE.txt文件。运行步骤　（计算PK SK R）－－＞（A_RSA加密）－－＞（A_RSA解密）。 -1. First, it is necessary folder of documents copied to rsa.c running tools (eg TURBOC2) folder called INCLUDE of folders. (In this plane has been done, so there was no need to do) 2. RSA encryption target for the C-CODE.txt document, entitled under the former eight (if not necessarily in the C - to establish a document titled CODE.txt documents, the encrypted data to document wrote), encryption in the next generation C-1 document, entitled RSACIPER.txt document. (In this plane has been done, so there was no need to do the above two-step) but on the other machine had to complete the above two steps before running. 3. RSA decryption target for the C-under File Name RSACIPER.txt documents, declassified after the C-Descent into End_CODE.txt document. Run steps (PK calculated SK R )-->( A_R
Update : 2008-10-13 Size : 3.68kb Publisher : 杨
[Other resource] fouriertransmation DL : 0: 图像处理证明二维夫里叶变换等价于两步一位傅里叶变换的程序-image processing proved two Weaver Fourier Transform equivalent to a two-step procedure Fourier Transform
Update : 2008-10-13 Size : 1.32kb Publisher : 窦秋盈
[Other resource] dingdianchengfaqisheji DL : 0: 目录: 0、约定 1、无符号数一位乘法 2、符号数一位乘法 3、布思算法(Booth algorithm) 4、高基(High Radix)布思算法 5、迭代算法 6、乘法运算的实现——迭代 7、乘法运算的实现——阵列 8、乘加运算 9、设计示例1 —— 8位、迭代 1、实现方案1 —— 一位、无符号 2、实现方案2 —— 一位、布思 3、实现方案3 —— 二位 10、设计示例2 —— 16位、阵列 11、设计示例3 —— 32位、迭代、阵列 1、实现方案1 —— 乘、加一步走 2、实现方案2 —— 乘、加两步走-Contents : 0, an agreement, an unsigned multiplication number two, a few multiplication symbols 3, Andrew Bruce algorithm (Booth algorithm) 4. Gao (High Radix), Andrew Bruce algorithm 5, 6 iterative algorithm, the realization of multiplication -- iterative 7, Implementation of multiplication -- Array 8, multiply-add nine, design examples 1 -- 8 spaces, an iterative, Implementation 1 -- one, two unsigned achieve program 2 -- 1, 3, Andrew Bruce, Implementation 3 -- 2 10 design examples 2 -- 16 spaces, 11 arrays, design examples 3 -- 32 spaces, iterative, an array achieve program 1 -- x, plus step two, achieving program 2 -- x, plus two-step
Update : 2008-10-13 Size : 373.74kb Publisher : 少华
[Fractal program] baioding-Tsai DL : 0: 此程序主要是用于二步法的摄像机标定，可以通过他得出内外参数-this procedure is used mainly to the two-step calibration can be reached through his internal and external parameters
Update : 2008-10-13 Size : 4.19kb Publisher : 让他
[Graph program] RAC-Tsai DL : 0: 这是个径向约束的二步法摄像机标定源程序，对于许多搞机器视觉的同志应该很有帮助的，欢迎参考-this is a radial bound two-step calibration source. For many engage in machine vision comrades should be helpful, please reference
Update : 2008-10-13 Size : 181.5kb Publisher : 嘉靖
[Other resource] showbitmap DL : 0: 位图装入、显示的c++类。使用方法： 1 构造类的一个实例对象：空实例 CDIB bmp() 用资源号构造 CDIB bmp(nResID) 用文件构造 CDIB bmp(\"PATH//Filename.bmp\") 2 若1步构造的是空实例对象，则须装入位图：从文件装入 BOOL bmp.LoadFromFile(\"PATH//Filename.bmp\") 从资源装入 BOOL bmp.LoadFromResource(UINT nResID) 3 画位图图象 Draw(CDC* pDC,目标图左上角x&y坐标,长&宽,原图象左上角x&y坐标) Draw(CDC* pDC,目标图左上角x&y坐标) Draw(CDC* pDC) Stretch(CDC* pDC, 目标图左上角x&y坐标,长&宽,原图像左上角x&y坐标,长&宽) 注： pDC的获取: CDC *pDC=GetDC() -bitmap loaded, shows the category c. Use : a structural example of a type of object : Air examples Bitmap bmp () with the resources, structure Bitmap bmp (nResID) document structure with CD IB bmp ( "PATH / / Filename.bmp") if a two-step structure of the object is empty examples , must be loaded bitmap : BOOL loaded from the file bmp.LoadFromFile ( "PATH / / Filenam e.bmp ") from the resource loading BOOL bmp.LoadFromResource (UIN T nResID) three paintings Bitmap Draw (CDC * pDC, objectives map upper left corner x
Update : 2008-10-13 Size : 10.92kb Publisher : linus
[Other] tsaiNEW DL : 0: 这是一个tsai两步法标定的源程序，它是以改进算法，对作摄像机标定的朋友会很有帮助-Tiberius This is a two-step calibration source, it is based on improved algorithm right for the camera calibration friends will be helpful
Update : 2008-10-13 Size : 161.07kb Publisher : 王占涛
[Other resource] knight DL : 0: 骑士遍历问题，在一个n*n个方格的国际象棋棋盘上，马（骑士）从任意指定方格出发，按照横1 步竖2 步，或横2 步竖1步的跳马规则，走遍棋盘的每一个格子，且每个格子只走1次。-Knight, in an n * n box at the international chess board, Ma (Knight) from the arbitrary designation box and, in accordance with a further horizontal two-step vertical, horizontal or a vertical two-step further vaulting horse rules traveled a checkerboard lattice of each and every one lattice just take time.
Update : 2008-10-13 Size : 1.33kb Publisher : 张三
[AI-NN-PR] Apriori DL : 0: Apriori算法是一种找频繁项目集的基本算法。其基本原理是逐层搜索的迭代，直到不能找到维度更高的频繁项集为止。这种方法依赖连接和剪枝这两步来实现。-Apriori algorithm is a frequent itemsets to find the basic algorithm. The basic principle is that the iterative search step by step, until a higher dimension can not find frequent itemsets ending. This method relies on a connection and pruning to achieve these two steps.
Update : 2025-02-19 Size : 19kb Publisher :
[matlab] EMfor_neural_networks DL : 0: 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. -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.
Update : 2025-02-19 Size : 193kb Publisher : 晨间
[SCM] step DL : 0: 单片机采用两相励磁的方式驱动四相步进电机-Single-chip using two-phase excitation mode four-phase stepper motor driver
Update : 2025-02-19 Size : 1kb Publisher : 王彦
[Software Engineering] ImageProcessing-CircleDetection-RenatoSalas_final DL : 0: The present report outlines the design, implementation and performance of the application of Hough Transform (HT) to detect circles in arbitrary pictures. Detecting circles in arbitrary pictures involves a two step process in this project. First, edges within the image have to be detected then, by means of a voting mechanism the most probable circles will be located. Edge detection goal is to look for boundary locations that naturally happen between objects. Objects normally have continuous intensity values therefore sudden changes in that pattern might indicate a boundary condition. Changes of intensity in one direction can be calculated by the gradient operator however, noise can alter meaningful edges. Convolution is then normally applied to account for a small amount of smoothing, thus reducing noise.-The present report outlines the design, implementation and performance of the application of Hough Transform (HT) to detect circles in arbitrary pictures. Detecting circles in arbitrary pictures involves a two step process in this project. First, edges within the image have to be detected then, by means of a voting mechanism the most probable circles will be located. Edge detection goal is to look for boundary locations that naturally happen between objects. Objects normally have continuous intensity values therefore sudden changes in that pattern might indicate a boundary condition. Changes of intensity in one direction can be calculated by the gradient operator however, noise can alter meaningful edges. Convolution is then normally applied to account for a small amount of smoothing, thus reducing noise.
Update : 2025-02-19 Size : 1.06mb Publisher : donna
[matlab] opt DL : 0: 实现单纯形法求解最优化问题的步骤，两步法实现，可自由输入参数-Simplex method to achieve optimization step, two-step implementation of free input parameters
Update : 2025-02-19 Size : 2kb Publisher : shenji
[matlab] two-step-encryption-and-decryption DL : 0: 实现了两步相移的基于随机相位掩码的图像加密和解密-To achieve a two-step phase shift mask image based on random phase encryption and decryption
Update : 2025-02-19 Size : 1kb Publisher : 刘辉龙
[AI-NN-PR] Multi-step-prediction-of-chaotic DL : 0: Multi-step-prediction of chaotic time series based on co-evolutionary recurrent neural network 协同进化递归神经网络的多步混沌时间序列预测-This paper proposes a co-evolutionary recurrent neural network (CERNN) for the multi-step-prediction of chaotic time series, it estimates the proper parameters of phase space reconstruction and optimizes the structure of recurrent neural networks by co-evolutionary strategy. The searching space was separated into two subspaces and the individuals are trained in a parallel computational procedure. It can dynamically combine the embedding method with the capability of recurrent neural network to incorporate past experience due to internal recurrence. The eﬀ ectiveness of CERNN is evaluated by using three benchmark chaotic time series data sets: the Lorenz series, Mackey–Glass series and real-world sun spot series. The simulation results show that CERNN improves the performances of multi-step-prediction of chaotic time series.
Update : 2025-02-19 Size : 149kb Publisher :
[Algorithm] two-stepQRmethod DL : 0: 对于一个10乘10矩阵，先拟上三角化，再用带双步位移的QR方法求矩阵的特征值（包括复数特征值），再用列主元高斯消去法求矩阵的特征向量。-For a 10 by 10 matrix, first proposed on the triangulation, and then with a two-step displacement of the QR method, to calculate the eigenvalues of the matrix (including the complex eigenvalues), then the main element column matrix of the Gaussian elimination method for the eigenvectors.
Update : 2025-02-19 Size : 471kb Publisher : 朱付涛
[Special Effects] two-step-iterative-shinkage DL : 0: 图像复原中的two-step iterative shinkage方法-two-step iterative shinkage
Update : 2025-02-19 Size : 7kb Publisher :
[Graph program] Twostep_spotlight DL : 0: 聚束模式的两步成像算法MATLAB程序，可以直接运行(Spotlight mode of the two step imaging algorithm MATLAB program, you can run directly)
Update : 2025-02-19 Size : 6kb Publisher : 摩羯

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