xingyouxian

此程序为将a律13折线的PCM信号，进行采样量化输出，和其中的量化精度可达0.01(This procedure will be a law broken line 13 of the PCM signal sample quantization output, and the quantitative accuracy of 0.01)

说明：  在用混沌理论和神经网络进行短期负荷预测时，神经网络的输入的选择至关重要，该程序用matlabl实现了基于混沌时间序列的嵌入维数的选择(In chaos theory and neural networks with short-term load forecasting, neural network is essential to choose the input, the program implemented with matlabl chaotic time series based on the number of choices of embedding dimension)

MPC模型预测控制算法应用在风电场功率波动平抑的典型案例，参考意义(The MPC model predictive control algorithm is applied in the typical case of wind farm power fluctuations )

用Matlab程序， 播放世界名曲卡农 播放世界名曲卡农播放世界名曲卡农 (Matlab play world music canon)

精通Matlab与C/C++ 混合程序设计(第2版)(Proficient in Matlab and C/C++ mixed program design (2nd edition))

说明：  数据结构的C++描述，书中的第三章的上机代码。大家可以自由参考下。(The C++ data structures described in the book' s third chapter on the native code. Members are free to refer to the following.)

用镜像矩阵求出矩阵的QR分解（正交三角分解），并求解线性方程组，该方法不必选主元，但其计算过程非常稳定。也可用于求矩阵的广义逆和求解线性最小二乘问题。子过程QRDCMP用镜像矩阵求m*n矩阵A的QR分解，A=Q^TR,其中Q是m*m正交矩阵，R为m*n上三角矩阵；子过程QRBKSB用矩阵的QR分解求解线性方程组Ax=b，其中A为n阶非奇异方阵。(Matrix obtained with the mirror matrix QR decomposition (orthogonal triangular decomposition), and solving linear equations, the method does not have to choose the main element, but its calculation process is very stable. Can also be used to find the generalized inverse matrix and solving linear least squares problems. Sub-process of the mirror matrix QRDCMP m* n matrix A QR decomposition, A = Q ^ TR, wherein Q is a m* m orthogonal matrix, R is m* n upper triangular matrix subprocess QRBKSB a QR decomposition to solve the matrix linear equations Ax = b, where A is non-singular square matrix of order n.)

这个就是MU的原版客户端文件里的ITEM备份，可以用来修改(Clients original files, you can back up with it, ha ha ha ha ha ha ha ha)

利用MATLAB模拟的细胞自动机程序，可以借用来研究怎么写此类程序(Using MATLAB simulation of cellular automata program, you can borrow to study how to write such programs)

一个介绍matlab的课件，介绍初等模型的，相信对大家都有用处的，很好的课件。(An introduction matlab courseware to introduce elementary model, I believe we have useful, well courseware.)