shot

视频监控，如果有东西经过监控区域就语音报警（有贼闯入）利用帧之间做差的方法(Video surveillance, if there are things after monitoring the regional voice alarm (the thief broke into) the use of the frame do the difference between method)

说明：  利用costas环实现载波同步的matlab程序，载频10mHz(Costas loop to achieve carrier synchronization using the matlab program, carrier frequency 10mHz)

希尔伯特黄变换的源代码及其MATLAB软件包(HHT code)

窗函数法设计数字滤波器 矩形窗、海宁窗、汉明窗和布莱克曼窗 滤波特性(Window function method to design digital filters rectangular windows, Haining window, Hamming window and Blackman window filtering properties)

非线性整数规划算法，求解非线性整数规划活混合规划问题，常用的算法是分枝定界算法。基于该算法编成的现成函数bnb20()(Nonlinear integer programming algorithm for solving nonlinear mixed integer programming live planning problem, commonly used algorithms are branch-and-bound algorithm. Based on the algorithm into off-the-shelf function bnb20 ())

用数值方法实现该fsk信号的相关型解调器，完成一个二进制fsk通信系统的仿真(Numerical methods used in the implementation of the relevant type fsk signal demodulator, to complete a binary fsk communication system simulation)

说明：  利用matlab编写的小波分解分频和除躁程序，分为高低频率，并除去噪声，达到较好的效果。(Prepared using matlab wavelet decomposition impatient frequency and in addition to procedures, divided into high and low frequency, and to remove noise, to achieve good results.)

是一个开发的小的matlab程序，自我感觉不错，和大家分享一下。(Is a development of small matlab program, self-feeling good, and everyone to share.)

matlab transformed to C++. Eigenvalue

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.