da903x

在一个自己设置的已知障碍的环境下，用势场法做路径规划，起点，目标位置都是已知。我用matlab做的(themselves in a set of known obstacles to the environment, with potential field do path planning, the starting point, target locations are known. I used Matlab to do)

QAM is quadrature amplitue modulation...in wireless communication...this code is used to control the exceeding power of some mobile users..

说明：  梯度下降法是一個一階最佳化算法，通常也稱為最速下降法。 要使用梯度下降法找到一個函數的局部極小值，必須向函數上當前點對應梯度（或者是近似梯度）的反方向的規定步長距離點進行疊代搜索。如果相反地向梯度正方向疊代進行搜索，則會接近函數的局部極大值點；這個過程則被稱為梯度上升法。(The gradient descent method is a first-order optimization algorithm, also commonly referred to as the steepest descent method. To find the local minimum of a function using the gradient descent method, an iterative search must be performed to the specified step distance point in the opposite direction of the gradient (or approximate gradient) of the current point on the function. If the search is reversed in the opposite direction to the positive direction of the gradient, it will approach the local maximum point of the function; this process is called the gradient ascent method.)

简单潮流计算：应用牛顿拉夫逊法。可以准确得到各节点电压向量大小，首末端功率，支路功率损耗(Simple flow calculation: The Newton Raphson method. Can get the exact size of the node voltage vector, the first end of the power, slip power loss)

说明：  一是讲述MATLAB正常运行所必须具备的基础条件；二是简明系统地介绍高度集成的Desktop操作桌面的功能和使用方法。(One is about the normal operation of the MATLAB must have the basic conditions Second concise introduction to a highly integrated system Desktop operating desktop features and applications.)

All about the digital modulations ASK, FSK, QPSK

matlab 鼠标从一幅图像中截取一个区域，并生成一幅图片(get a picture form a picture)

matlab实现软硬阈值函数的图像去噪，附带一张测试图片矩阵lenna.mat(matlab image denoising hard and soft threshold function, with a test image matrix lenna.mat)

lagre no of m file for matlab course code file # 4(lagre no of m file for matlab course code file# 4)

a design methodology is introduced that blends the classical PID and the fuzzy controllers in an intelligent way and thus a new intelligent hybrid controller has been achieved. Basically, in this design methodology, the classical PID and fuzzy controller have been combined by a blending mechanism that depends on a certain function of actuating error. Moreover, an intelligent switching scheme is induced on the blending mechanism that makes a decision upon the priority of the two controller parts namely, the classical PID and the fuzzy constituents. The simulations done on various processes using the new hybrid fuzzy PID controller provides ‘better’ system responses in terms of transient and steady-state performances when compared to the pure classical PID or the pure fuzzy controller applications. The controller parameters are all tuned by the aid of genetic search algorithm.