Matlab-OF-MATHMATIC

gsc 广义旁瓣消除器的MATLAB源程序(gsc GSC MATLAB source device)

分别设计理想低通滤波器、巴特沃思滤波器、指数滤波器、梯形低通滤波器,并对含高斯噪声的图像进行低通滤波，截止频率自选，观察不同的截止频率,不同的滤波器的滤波效果。(Were designed for the ideal low pass filter, Butterworth filter, exponential filter, ladder low-pass filter, and Gaussian noise images with low-pass filter cutoff frequency chosen to observe the different cut-off frequency, different filter filtering device.)

卫星轨道仿真，源码，C++，定位等信息GEllipticalOrbit.cpp登文件(Satellite orbit simulation )

5G 技术 NOMA 运用ZF SIC 可简单使用(NOMA with ZF SIC)

自己编写的一个matlab实现手写数字的识别，识别率高达90 以上。(I have written a matlab achieve recognition of handwritten digits recognition rate of 90 .)

使用matlab绘心形图画，利用弧线画花萼、花瓣等花的细节信息，表白专用(Use matlab heart-shaped picture painted by the arc drawn sepals, petals and other floral details, declare special)

一个基于增量反馈的广义预测控制算法的matlab程序，程序说明详细(A feedback based on incremental generalized predictive control algorithm matlab program, detailed description of the procedures)

稳态kalman滤波算法仿真通式 本程序考虑线性离散时不变随机系统。系统模型为x(t+1)=fai*x(t)+gama*w(t) y(t)=H(t)*x(t)+v(t)。有6个参数：状态转移阵fai，输入噪声系数gama，观测阵H，输入 噪声方差Q，观测噪声方差R，观测y( Steady-state kalman filtering algorithm simulation program to consider the general form linear discrete time-invariant stochastic system. System model x (t+1) = fai* x (t)+ gama* w (t) y (t) = H (t)* x (t)+ v (t). There are six parameters: state transition matrix fai, input noise figure gama, observation matrix H, enter noise variance Q, observation noise variance R, observation y)

Pattern search (also known as direct search, derivative-free search, or black-box search) is a family of numerical optimization methods that does not require a gradient. As a result, it can be used on functions that are not continuous or differentiable. One such pattern search method is "convergence" (see below), which is based on the theory of positive bases. Optimization attempts to find the best match (the solution that has the lowest error value) in a multidimensional analysis space of possibilities.

matlab函数列表以及功能说明，非常实用(matlab function lists, and feature descriptions, very useful)