Kanxxx1

说明：  QPSK详细调制解调的源码，包括整个流程．(QPSK modulation and demodulation of the source in detail, including the entire process.)

doppler effect simulation in matlab

数字信号处理 Digital signal processing(Digital signal processing Digital signal processing)

XCODE超级玛丽，部分oc，部分c++(SuperMario，made by xcode)

一篇介绍matlab实现高效编程的文档，对于每一种方法都有相关的例子(An efficient introduction matlab programming documents, for each method are related to the case)

在VC中用Matlab引擎计算实对称矩阵特征值和特征向量。.mor0为矩阵输入文件，.mor位结果输出文件。(Calculated using Matlab engine in the VC real symmetric matrix eigenvalues ​ ​ and eigenvectors. . Mor0 matrix input files,. Mor-bit result output file.)

压缩感知里面的稀疏重建问题，在原来MP的算法的基础上，提出了分块的思想，即将原子库分块后，测试算法的性能。(Compressive sensing is refered as the block sparse algorithm is described,that is based on the original MP algorithm,and the atom libruary is divided into blocks ,and the performance is testified.)

This program is my homework of pattern recognition, it is a source code of PCA program by matlab.

说明：  用Matlab绘制TEQC结果图形的程序(The results using Matlab graphics rendering procedures TEQC)

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.