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这是模型检测的一个最新版本，希望对大家有所帮助。(This is one of the latest version of model checking, we want to help.)

一个模糊控制表，里面完成了一个模糊控制，实现了simulink仿真，可供初学者学习模糊控制及matlab。(A fuzzy control table, which completed a fuzzy control to achieve the simulink simulation available for beginners learning fuzzy control and matlab.)

说明：  用matlab观察DOG小波时域和频域波形(using Matlab observation DOG wavelet time domain and frequency domain waveform)

二值图像的膨胀与腐蚀函数matlab源代码(binary image dilate and erode)

归一化LMS算法，自己更改参考信号和期望信号(normalized LMS algorithm，change the reference signal and desired signal by yourself)

ant colony algorithm for tsp problem

使用重构向空间捕捉非线性特征。来源于国外网站，请注明出处。(RPS Toolbox - This toolbox contains Matlab functions to capture the nonlinearities of the speech production system using reconstructed phase space (RPS) techniques.)

Used to annotate a method parameter to indicate that this method will close the resource.

将Excel里面的大量数据导入MATLAB软件里面进行画图(A large amount of data in Excel is imported into MATLAB software for drawing)

The cable compensation system is an experiment system that performs simulations of partial or microgravity environments on earth. It is a highly nonlinear and complex system.In this paper, a network based on the theory of the Fuzzy Cerebellum Model Articulation Controller(FCMAC) is proposed to control this cable compensation system. In FCMAC ,without appropriate learning rate, the control system based on FCMAC will become unstable or its convergence speed will become slow.In order to guarantee the convergence of tracking error, we present a new kind of optimization based on adaptive GA for selecting learning rate.Furthermore, this approach is evaluated and its performance is discussed.The simulation results shows that performance of the FCMAC based the proposed method is stable and more effective. (The cable compensation system is an experiment system that performs simulations of partial or microgravity environments on earth. It is a highly nonlinear and complex system.In this paper, a network based on the theory of the Fuzzy Cerebellum Model Articulation Controller (FCMAC) is proposed to control this cable compensation system. In FCMAC, without appropriate learning rate, the control system based on FCMAC will become unstable or its convergence speed will become slow.In order to guarantee the convergence of tracking error, we present a new kind of optimization based on adaptive GA for selecting learning rate.Furthermore, this approach is evaluated and its performance is discussed.The simulation results shows that performance of the FCMAC based the proposed method is stable and more effective.)