卷积神经网络CNN代码解析-matlab

说明：  详细阐述了线性矩阵不等式的方法，并用一个实际例子，用matlab实现了,对初学者非常有用.(Described in detail the method of linear matrix inequalities, and a practical example, using matlab realized, very useful for beginners.)

简单明了的CSS教程，可供网站开发人员的快速参考。-straightforward CSS guidance for the development of the site for quick reference.

Java source code examples, RadioButton instance!

说明：  实现简单的领航跟随编队控制，能够改变队形，以及航迹(Achieve simple leader_following formation control, which is able to change formation, track and num of robots)

电池管理系统BMS的一个小开发板，附原理图就说明资料(Battery management system BMS a small development board, with schematics on the information)

基于pscad搭建的三相脉波整流程序，可直接运行，也可将此修改后作为AC/DC模块。(The three-phase pulse rectifier based on PSCAD can be run directly, or it can be modified as AC/DC module.)

用简单的YACC描述一个互交的计算器,该计算器有26个寄存器-YACC simple description of an interactive calculator, the calculator has 26 registers

深入理解Python中文版-啄木鸟 深入理解Python中文版-啄木鸟(Depth understanding of the Chinese version of Python- Python-depth understanding of the Chinese version Woodpecker- Woodpecker)

用外积和法设计的权矩阵，不能保证p对模式全部正确的联想。若对记忆模式对加以限制（即要求p个记忆模式Xk是两两正交的），则用外积和法设计的BAM网具有较好的联想能力。 在难以保证要识别的样本（或记忆模式）是正交的情况下，如何求权矩阵，并保证具有较好的联想能力？这个问题在用BAM网络实现对字符的识别程序仿真中得到体现。我们做过尝试，用伪逆法求权矩阵，虽然能对未加干扰的字符全部进行识别，但对加有噪声的字符识别效果很差。至于采用改变结构和其他算法的方法来求权矩阵，将是下一步要做的工作。-foreign plot and the design of the power matrix, p is no guarantee that all the correct pattern association. If memory model, the limit (that is, p-memory model Xk is orthogonal to the February 2), then foreign plot and design of the BAM network has good ability to think. It is difficult to ensure the samples to identify (or memory mode) is orthogonal circumstances, the right to seek ways matrix, and to ensure that the association has good ability? The problem with the BAM network of characters identification procedures simulation can be manifested. We did try to use pseudo- inverse matrix for the right, although they would not increase the interference of the characters in the identification of all, However, a pair of noise increases the effects o

说明：  用卡尔曼滤波方法进行GPS静态和动态定位数据的处理。分别建立静态及动态模型及滤波方程，简述动态模型与静态模型的区别与联系；讨论R阵、Q阵，P0阵的选取对滤波精度及收敛速度有何影响，取值时应注意什么；讨论本滤波问题是否可以用最小二乘方法解决。(Kalman filter is used to process GPS static and dynamic positioning data. Establish static and dynamic models and filtering equations respectively, briefly describe the difference and connection between dynamic model and static model; discuss how the selection of R matrix, Q matrix and P0 matrix affects the filtering accuracy and convergence speed, and what should be paid attention to when taking values; discuss whether the filtering problem can be solved by the least square method.)