DC-PM-motor

This simulation shows the effective SNR verse subcarrier number as a result of band pass filtering of the signal

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.

Stephen J.Chapman《MATLAB编程（第二版）》,希望对大家有所帮助。(Stephen J. Chapman )

design inverter pol 3 phase

详解matlab/simulink通信系统建模与仿真的教案(Detailed matlab/simulink communications system modeling and simulation lesson plans)

The “INVERTED PENDULUM, ANALYSIS, DESIGN AND IMPLEMENTATION” is a collection of MATLAB functions and scripts, and SIMULINK models, useful for analyzing Inverted Pendulum System and designing Control System for it.

All estimator filter kalmans

separation nonlineaire de source par iteration

这是智能天线设计一书中的源码，有详细的代码注释。(This is the design of smart antenna in a Book of the source code, a detailed code comments.)

说明：  详细研究了单级倒立摆起摆控制方法，并给出了详细的仿真模型与仿真效果(Detailed study of the single inverted pendulum swing-up control method, and gives a detailed simulation model and simulation results)