SSD1306SimpleDemo3_reset

说明：  利用Pytorch实现的一个简单的神经网络，实现了异或门。(Using a simple neural network implemented by Pytorch, XOR gates are realized.)

大量的vc界面编程源码-lot of vc-source programming interface

We now compare our method to prior stochastic configurations solutions [19]. This methods

简单介绍下基于粒子滤波的目标跟踪算法，希望可以帮助到一些想入门的人(A brief introduction to particle tracking based target tracking algorithm)

一种基于局部密度的离群检测方法，一篇神经计算期刊的源代码，转自GitHub(An outlier detection method based on local density, a source code of a neural computing journal, transferred from GitHub)

6个C# TreeView树形菜单控件，制作树形菜单用得上哦，分别是：Clifton.Tools.Compiler、Clifton.Tools.Data、Clifton.Tools.Xml、Clifton.Tools.Strings、Clifton.Windows.Forms、GeneralTreeDemo。示例运行效果如截图所示。

LCD1602显示+串口接收温度该程序从串口接收数据，通过LCD显示数据。在LCD的第一行显示出来,     当数据过多时（超过16个字符），LCD第一行将会被覆盖。

说明：  在LABVIEW 程序案例，程序运行中改变菜单，变量修改，(Change menu during program running)

基于人工智能方面的，运用极大极小算法的井字棋源代码-Based on artificial intelligence aspects, the use of max-min algorithm source code for tic-tac-toe game

MPCPY是一个Python程序包，它有助于测试和实现用于构建系统的乘员集成模型预测控制（MPC）。该软件包侧重于使用数据驱动的、简化的物理或统计模型来预测建筑性能和优化控制。四个主要模块包含对象类来导入数据，与真实的或仿真的系统交互，估计和验证数据驱动的模型，并优化控制输入。(MPCPy is a python package that facilitates the testing and implementation of occupant-integrated model predictive control (MPC) for building systems. The package focuses on the use of data-driven, simplified physical or statistical models to predict building performance and optimize control. Four main modules contain object classes to import data, interact with real or emulated systems, estimate and validate data-driven models, and optimize control input.)