dflux热源加载

VC++为图片增加水波鼠标跟随效果的特效蒙版，动态的图片蒙版，鼠标在图片上晃动，会随机出现水波效果，晃动的越快，水波越多哦。用户还可以选择火焰和等离子效果，类似于给图片增加了一层蒙版的效果，很给力。

本例的源描述超过了演示版限制的300行, 如果您需要对其进行编译与模拟,请与北京理工大学 ASIC研究所联系,获取Talent系统的完全版本. 联系方法: 电话:010-68912434 信函:北京理工大学ASIC研究所 刘明业 教授收 邮编:100081-The source described in this case than the demo version of the 300 line limit, if you need to be compiled with the simulation, please contact ASIC Institute of Beijing Institute of Technology to obtain the complete version of Talent system. Contact: Tel :010-68912434 letter : Research Institute of Beijing Institute of Technology Professor Liu Mingye ASIC received Postcode: 100081

汽车碰撞仿真程序，一维二维汽车碰撞前后速度计算以及仿真(Automobile crash simulation)

说明：  本文档为PSCAD与电弧相关的模型介绍，包括断路器合闸、分闸、电弧模块及电弧重燃木块(This document is an introduction to PSCAD and arc related models, including circuit breaker closing, opening, arc module and arc reburning block)

RBF网络训练程序C++源代码，可以完成网络训练和网络测试功能。-RBF the network training procedure C source code, may complete the network training and the network test function.

矩阵链表堆栈8_1.rar 大学生课程设计-Matrix list stack 8_1.rar Students Course Design

FFT频偏估计算法，性能不错，用于GMSK调制(FFT frequency offset estimation algorithm, good performance, for GMSK modulation)

实现用msp430单片机发送AT指令控制sim300进行gprs通信(Implementation of GPRS communication with 430 control SIM300)

说明：  用N来表示训练用例（样本）的个数，M表示特征数目。 输入特征数目m，用于确定决策树上一个节点的决策结果；其中m应远小于M。 从N个训练用例（样本）中以有放回抽样的方式，取样N次，形成一个训练集（即bootstrap取样），并用未抽到的用例（样本）作预测，评估其误差。 对于每一个节点，随机选择m个特征，决策树上每个节点的决定都是基于这些特征确定的。根据这m个特征，计算其最佳的分裂方式。 每棵树都会完整成长而不会剪枝，这有可能在建完一棵正常树状分类器后会被采用）。(N is used to represent the number of training cases (samples), and M is used to represent the number of features. The number of input features m is used to determine the decision result of a node in the decision tree, where m should be far less than m. From N training cases (samples), n times are sampled in the way of put back sampling to form a training set (i.e. bootstrap sampling), and the unselected cases (samples) are used to predict and evaluate the error. For each node, m features are randomly selected, and the decision of each node in the decision tree is determined based on these features. According to these m characteristics, the best splitting mode is calculated. Each tree will grow completely without pruning, which may be adopted after building a normal tree classifier).)

说明：  QT小程序，一个简单的QT程序，可以下载试试，初学QT适合(QT applet, a simple QT program, you can download it to try, the initial learning of QT is suitable.)