A3111

说明：  是电力系统的电磁暂态仿真用的EMTP中的免费版ATPDraw，主要是应用于交直流的暂态仿真，这是图形界面版的(this is power system software)

VB程序中实现调用MATLAB的方法. 介绍了在VB 应用程序中利用动态数据交换和ActiveX自动化(OLE自动化)协议实现的两种调用MATLAB函数的方法。通过这两种方法实现了VB的可视化界面与MATLAB 强大的数值分析和图形显示的能力的结合。(Introduced in VB application using Dynamic Data Exchange and ActiveX Automation (OLE Automation) protocol calls MATLAB function of the two methods. Achieved by either method, the visual interface of VB and MATLAB powerful numerical analysis and graphical display of the ability of combination.)

A DC to DC Boost Converter

评价算法。神经网络一个很好的应用。。。。。大家可以看看！(Evaluation algorithm. Neural network a very good application. . . . . Everyone can see!)

灰预测控制器的MATLAB研究，并利用MATLAB语言编程(Grey prediction controller MATLAB studied using MATLAB programming language)

拉格朗日插值，利用拉格朗日法进行插值计算，欢迎下载，谢谢(lagrange interp)

天线三维仿真，得出具体图谱，吃三个图有具体含义(Three-dimensional simulation of the antenna, to draw concrete map, three graphs have a specific meaning to eat)

由matlab平台实现,是一种提取共振峰信息的有效方法.(from Matlab platform is a resonance peak extraction of information in an effective manner.)

说明：  一个dbn例子函数，dbntrain,用于设置训练相关的参数。(a dbntrain function for dbn.It is used for set the train para.)

Q-learning (Watkins, 1989) is a simple way for agents to learn how to act optimally in controlled Markovian domains. It amounts to an incremental method for dynamic programming which imposes limited computational demands. It works by successively improving its evaluations of the quality of particular actions at particular states. This paper presents and proves in detail a convergence theorem for Q,-learning based on that outlined in Watkins (1989). We show that Q-learning converges to the optimum action-values with probability 1 so long as all actions are repeatedly sampled in all states and the action-values are represented discretely. We also sketch extensions to the cases of non-discounted, but absorbing, Markov environments, and where many Q values can be changed each iteration, rather than just one.