cloud_model

本程序可以产生一组正态模拟数，用来模拟实际生产中服从或近似服从正态分布的数据，很有用。(This procedure can generate a group of normal simulation the number used to simulate the actual production or similar to obey normal distribution of data, very useful.)

funny factorial and description

A New Algorithm for the Reconfi guration of Distribution

灰度图像的直方图均衡化以及rgb图像的均衡化(Gray-scale image histogram equalization and the equalization of rgb images)

电力系统谐波监测相关的文章其中的fft和apfft之间的对比很有参考意义(Fft and apfft contrast between the power system harmonic monitoring related article which is very useful)

M序列信号算法仿真在系统辨识中有着很大的应用前景。多谐差相方法辨识精度很高有着很苛刻的要求，要求已知辨识参数个数已知并且需要整周截断。而M序列信号的测试方法没有这个方面的要求。其辨识未知模型时，可以用最小二乘算法观察辨识系统的精度来确定模型的阶次。本算法里面不但给出了用于M序列生成的本原多项式计算方法，同时编写了M序列信号的生成算法，并编写了相关辨识方法的算法。(M sequence signal simulation algorithm for identification in the system have great application prospects. Identification of multi-harmonic differential phase method with high precision has very stringent requirements, demand parameters are known to identify the number of known and need to cut off the whole week. The M sequence signal testing methods do not have this requirements. Its identification unknown model, you can observe the identification system using least-squares algorithm to determine the accuracy of the model order times. This algorithm is used which not only gives the M sequence generated by primitive polynomial method of calculation as well as prepare the M sequence signal generation algorithm, and the preparation of the relevant identification method algorithms.)

说明：  一些有关最优控制理论的控制实例程序集和仿真 (Control instance assembly of the optimal control theory and simulation)

声谱图+共振峰,有中文的注解, 像Praat(spectrogram+ Formant, Code has Chinese comments)

本自适应算法，是格型的LMS算法，描述了反射系数对算法的影响，以及LMS算法和格型LMS算法的对比(The adaptive algorithm is grid-based LMS algorithm, the algorithm describes the impact of the reflection coefficient, and the LMS algorithm and lattice LMS algorithm comparison)

说明：  基于MATLAB的BP神经网络非线性映射能力实现图像压缩。(MATLAB Based on BP neural network nonlinear mapping capability for image compression.)