Matlab

ANN的MATLAB实例详解，通过对matlab语言如何编程进行实例解析，是学习ANN的很好教程(Detailed examples of ANN in MATLAB through the matlab programming language for examples of how to resolve, are a good ANN Study Guide)

瑞历信道下误码率估计的盟特卡罗仿真，GUI显示，方便高效(Switzerland calendar channel bit error rate estimated UNITA Carlo simulation, GUI, facilitate efficient)

matlab 模式识别识别数据，循环处理(Matlab pattern recognition to identify data processing cycle)

modelseis, seismic modeling forward and inverse modeling,

自己编写的程序，能够实现单变量的线性回归，随机产生训练样本，利用梯度下降法实现训练过程，并且画出了误差的迭代曲线。(I have written a program that can achieve single-variable linear regression, random training sample using gradient descent method to achieve the training process, and draw the iterative curve errors.)

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.

802.15.4仿真IEEE802_15_4_Matlab-master

约束优化问题的matlab 多个元程序(Constraints multiple element program matlab)

Matlab document about induction motor softstart

二阶Volterra模型系统辨识，数据拟合，压缩包中带数据(Of Volterra model system identification, data fitting, with data compression package)