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MATLAB经典GUI源程序,适合初学者入门学习(MATLAB classic GUI source code, suitable for beginners learning portal)

The latest Matlab releases (starting with R2007a) include support for multiple cores. However, Matlab will only take advantage of multiple cores in evaluating certain computations like an FFT or a FIR filtering operation. Matlab will never be able to determine if, for example, consecutive function calls in a for-loop are independent of each other.

四阶龙格库塔数值方法，用于求解光纤光栅非线性耦合模方程，可求解正向，反向传输波幅度(Fourth-order Runge-Kutta solution of the coupled mode equation)

绘制椭圆，输入为椭圆中心坐标，方向，角度(drawing ellipse)

进行特征选择，利用权重进行特征选择，代码解释充分(Feature selection is carried out, feature selection is carried out with weight, and the code is fully interpreted.)

0:边界延拓镜像法 1:边界延自适应波形匹配法(boundary conditions)

模糊控制及其MATLAB应用，本书从工程应用与实践的角度，对模糊推理与模糊控制系统做了深入浅出的介绍，并以多个实例详细介绍模糊推理学习及其在matlab模糊推理工具箱中的实现(Fuzzy Control and MATLAB applications, engineering applications and practice book from the perspective of fuzzy reasoning and fuzzy control system to do a simple introduction, and more detailed examples of its application in fuzzy inference learning matlab fuzzy inference toolbox achieve)

说明：  通过分析交通流量时间序列的特点，引入BP神经网络进行短时交通流预测。首先，分析了短时交通流量预测的意义及研究背景；然后，介绍了BP神经网络的结构模型、学习规则以及BP算法的改进算法；最后，通过BP神经网络对短时交通流进行预测，并分析了在各种不同条件下的预测情况。(through the analysis of the characteristics of traffic flow time series, introduces BP neural network for short-term traffic flow prediction. First of all, it analyzes the significance of short-term traffic flow prediction and research background. And then, it has discussed the model and structure, the study rule and the improved algorithm of BP neural network. Finally, by BP neural network to forecast the short-term traffic flow, it analyzes under different conditions of the neural network prediction.)

2011-zhang-Dynamic Modeling of Scraper Conveyor Sprocket

单件模块，包括单件类和单件宏，使用单件宏能够从一个类(orgClassName)派生出一个单件类(newClassName)，并保持基类的功能。 (Single module, including a single category and single-hong, the use of a single category from a macro (orgClassName) derived from a single category (newClassName), and maintain the functions of base class.)