AY90S2313 AVR Promer

类似J2000的ECI坐标系转换到类似wgs84的ECEF坐标系,方便大家应用(Convert ECI (CIS, Epoch J2000.0) Coordinates to WGS 84 (CTS, ECEF) Coordinates. This function has been vectorized for speed. Example Function Call: >> [r_ECEF v_ECEF a_ECEF] = ECItoECEF(JD,r_ECI,v_ECI,a_ECI); Where: JD is the Julian Date vector [1 x N] (units are in days) r_ECI is the position vector [3 x N] (any units are permitted) v_ECI is the velocity vector [3 x N] (any units are permitted) a_ECI is the acceleration vector [3 x N] (any units are permitted))

说明：  STC8G系列的OLED驱动 7引脚OLED(OLED driver 7-pin OLED of stc8g series)

说明：  MATLAB蚁群算法机器人行驶路线紧急避碰(Ant colony algorithm)

说明：  基于遗传模拟退货的聚类算法,非常实用，可以直接运行(Clustering algorithm based on genetic simulation of returns is very practical and can be run directly)

旋转的地球flash特效，3维旋转的地球仪源码素材，3D地球Flash源文件，其实是用了两个层，不同的透明度和色度，向相反的方向运动，再用一个圆形遮罩，便可实现3D地球，当然了，这是比较简单的实现方法。

总个数确定后，每张盘curDisk的移动方向maybe_To是确定的且唯一的：如共有三个盘时，盘1始终向左移动。 这里，将柱子由左向右看成A(源柱子Source),B(借助的柱子Borrow),C(目标柱子Target). A的左看成C，B的左看成A，C的左看成B； A的有看成B，B的右看成C，C的右看成A； 每张盘的移动方法(因为不可能连续两次移动相同的盘！)： 一个盘curDisk现在在 柱子curStick上，那么curDisk另一个柱子(3个中除了2个的另1个) 只要有选择的选择一个柱子curStick,分析、判断其最上面的盘curDisk的能否向curDisk确定的唯一的方向移动；移动 完后 再 选择 另一个 柱子 分析 判断 就可以完成了 (这个算法特别适合于人玩这个“弱智”（我有同学这么说）游戏，我玩我的文曲星pc1000a上的Hanoi 9层游戏，需要5分钟就可以移动完毕)-total number identified, each set curDisk maybe_To direction of the movement of which is determined only : If there are three disk, was always left a mobile. Here, the columns from left to right as A (source pole Source), B (using the pole Borrow), C (target pole Target). A left as C, B to the left as A, C on the left as B; A as the B, B on the right side as C, the right as A; each set of mobile methods (as it is impossible for the same two mobile disk!) : a set curDisk curStick now on the pole, then curDisk another pole (three in addition to two other one), when given a choice, choose a pole

说明：  麦克风阵列增强入门资料，麦克风阵列语音增强算法研究(Introduction to Microphone Array Enhancement and Research on Microphone Array Speech Enhancement Algorithms)

：好风格应该成为一种习惯。如果你在开始写代码时就关心风格问 题，如果你花时间去审视和改进它，你将会逐渐养成一种好的编程习惯。一旦这种习惯变成 自动的东西，你的潜意识就会帮你照料许多细节问题，甚至你在工作压力下写出的代码也会 更好。(: Good style should become a habit. If you write code at the beginning when the issue of concern for style, if you take the time to examine and improve it, you will gradually develop a good programming practice. Once this habit becomes automatic things, your subconscious will help you take care of many details, and even under the pressure of your work will be better to write code.)

牧羊人服饰系统 (ADO+SQL) 第三方控件：advstringgrid，mxoutlookbarpro，ehlib3 是面向服装零售商店的销售系统 它包括调拨管理，销售管理，销售分析，店员操作记录管理，店员留言管理，退货管理,pos票据打印等模块。-shepherd costumes System (SQL ADO) third-party Controls : advstringgrid, mxoutlookbarpro, ehlib3-oriented retail clothing store marketing system including the allocation of its management, sales management, sales analysis, the staff members operating records management, shop assistants voice mail management, returns management, printing paper pos module.

CN对图像进行像素级的分类，从而解决了语义级别的图像分割（semantic segmentation）问题。与经典的CNN在卷积层之后使用全连接层得到固定长度的特征向量进行分类（全联接层＋softmax输出）不同，FCN可以接受任意尺寸的输入图像，采用反卷积层对最后一个卷积层的feature map进行上采样, 使它恢复到输入图像相同的尺寸，从而可以对每个像素都产生了一个预测, 同时保留了原始输入图像中的空间信息, 最后在上采样的特征图上进行逐像素分类。(CN classifies images at the pixel level, thus resolving the problem of semantic segmentation at the semantic level. Unlike classical CNN, which uses full-connection layer to get fixed-length feature vectors after convolution layer for classification (full-connection layer + soft Max output), FCN can accept any size of input image, and uses deconvolution layer to sample feature map of the last convolution layer to restore it to the same size of input image, so that each pixel can be generated. At the same time, the spatial information of the original input image is retained. Finally, the pixel-by-pixel classification is carried out on the feature map sampled above.)