psychoacoustic

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.

Simulation of the Logistic map n is the number of the simulated points. x is the simulated time series. a is the parameter.

用matlab处理音频, 对一段音频加入噪声然后滤除噪声还原, 绘制过程中的频谱图(Matlab deal with audio, for adding some audio noise reduction and filter noise, rendering the process of spectrum)

一种基于DCT变换的图像水印算法，非常适合研究水印的人们共同学习，共同进步。(DCT-based image watermarking algorithm)

Description of the file: template matching source of Chamfer matching algorithm. It s OpenCV implementation

编写matlab语言实现的bch编码程序(Write the BCH encoding program implemented in MATLAB language)

一个用于癌细胞形态学分析的Matlab程序，可用于Matlab学习。(One for cell morphology analysis, Matlab program can be used for learning Matlab.)

Double_buck_PI_Control.rar,功率电子领域matlab仿真文件，已经验证过，程序运行正常(Double_buck_PI_Control.rar,Power electronics field matlab simulation file, has already been verified, the normal operating procedures)

matlab MPC工具箱说明，英文比较详细(Matlab MPC toolbox instructions, English is a more detailed)

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