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这是一篇EI文献，关于机器视觉的BP神经网络的论文，针对多种水果混合的图像，对各种水果的提取和识别进行研究。利用Matlab软件进行图像数据获取、对比度增强、去噪、二值化处理；为弥补二值化后图像中出现的断边、孔洞，借助Sobel算子进行边缘提取以接合断边，并基于数学形态学算子填充孔洞。再标签化处理图像并提取水果的颜色、形状、边缘特征，用200幅水果图像提取上述特征构造训练样本和测试样本，然后利用构造的样本对BP神经网络进行训练和测试。实验结果表明,所提出的方法能够获得很高的正确识别率，能够有效地将同一幅图像中的不同水果识别出来。

台球地图实现，可以移植的模块，适合大多数的台球小程序，很方便-Billiard map realize, you can transplant the module, suitable for the majority of billiards applet, it is convenient

神龙卡播放MP4源代码，采用DSHOW开发技术-SHENLONG card MP4 player source code, using dshow Development Technology

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常用的盲分离算法有二阶统计量方法、高阶累积量方法、信息最大化（ Infomax ）以及独 立成分分析（ ICA ）等。这些方法取得最佳性能的条件总是与源信号的概率密度函数假设有关， 一旦假设的概率密度与实际信号的密度函数相差甚远，分离性能将大大降低。本文提出采用 核函数密度估计的方法进行任意信号源的盲分离，并通过典型算例与几种盲分离算法进行了 性能比较，验证了方法的可行性。(The commonly used blind separation algorithms include two order statistics, higher order cumulants, and maximization of information Infomax) and independent component analysis (ICA). The conditions for obtaining the best performance of these methods are always related to the hypothesis of the probability density function of the source signal. The separation performance will be greatly reduced when the assumed probability density is very different from the density function of the actual signal. In this paper, a method of kernel function density estimation for blind separation of arbitrary signal sources is proposed. The performance of several blind separation algorithms is compared with some typical examples, and the feasibility of the method is verified.)

实现了两电平逆变器上异步电机直接转矩控制仿真,引入了一种典型的直接转矩控制改进算法DSVM,并进行了仿真(DTC)

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工件加工问题，本程序提供了工件加工问题的一般算法question1 question2 question3经过调试能成功运行-workpiece machining, the process of machining the general algorithm question1 question2 question3 after the successful operation Debugging

Easy Language Indicator collection - Source code from A to C [TradeStation]

1.投票时免验证码输入，是绝大多数投票用户的强烈要求。">