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This matlab file explains the operation of Boost and buckboost converter with open loop as well as closed loop operation for voltage regulation and power factor improvement.

说明：  简单的画折线功能，单击右键示图取消，按住control键重置起点。(The painting features a simple broken line, right-click Diagram canceled, hold down the control key to reset the starting point.)

matlab下实现的波束形成技术，利用的是ETAM算法进行合成孔径，增加虚拟阵元个数，以提高定位精度。(matlab achieve beam forming technology, the use of the synthetic aperture ETAM algorithm to increase the number of the virtual array elements in order to improve positioning accuracy.)

code Matlab this is frome my data base

In this paper, a new approach based on the R, filtering is presented for speech enhancement. This approach differs from the traditional modified Wiener

FDTD-PML 算法的实现，效果好,大家一起研究，第一次上传，望指教(FDTD-PML method, with perfect results)

有关FM调制的实例，很有针对性，运行通过(FM modulation for instance, very targeted, run by)

数值分析课程设计，数字签名的设计，matlab条件下实现。(Numerical analysis curriculum design, the design of digital signature, matlab conditions realized. )

简单地支持向量机的测试程序，希望对你们有用,它是测试两个线性分类的。(A simple test program to support vector machine, and I hope useful to you.)

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.