DFT

说明：  包括模糊聚类分析数据各种标准化变换、模糊聚类分析建立模糊相似矩阵的各种方法(Fuzzy Cluster Analysis, including a variety of standardized data transformation, fuzzy cluster analysis to establish fuzzy similar matrix of the various methods)

即将于matlab的小波变换的示例工具箱，里面含有较多的示例程序(Toolbox upcoming matlab wavelet transform example, which contains more sample programs)

带算例的弧长法,可以对弧长法的运算模式有更加清晰的认识(arc-length with a verification examples)

MATLAB的典型应用,可以通过他很好的熟悉MATLAB,了解MATLAB的工作特性(Typical applications of MATLAB, you can very well through his familiarity with MATLAB, to understand the work characteristics of MATLAB)

MATLAB编辑的均衡器，八段式，功能很全面(MATLAB edited equalizer, eight very comprehensive)

LTE 系统级仿真 希望大家多多指教！！！！！(LTE SYSTEM LEVEL)

利用遗传算法求f(x,y)=x*cos(2*pi*y)+y*sin(2*pi*x),-2<=x<=2,-2<=y<=2的最大值(Using genetic algorithms for f (x, y) = x* cos (2* pi* y)+ y* sin (2* pi* x),- 2 <= x <= 2,-2 <= y <= 2 the maximum)

efilter & ffilter for Matlab imaging processing, which can be used in segmentation and reconstruction.

用局部参数最优化方法设计一个模型参考自适应系统,可调增益的初值Kc(0)=0.2，给定值r(t)为单位阶跃信号，即r(t)=A×1(t)。 要求： 1把连续系统离散化(采样时间可取0.1)。 2编制并运行这个系统的计算机程序(注意调整B值，使系统获得较好的自适应特性)。 3记录ym、yp的曲线 记录kp×kc的曲线 记录广义输出误差e的变化曲线。 4在参数收敛后，让Kp=2变为Kp=1，重新观察Kp×Kc及e的变化曲线。 5找出在确定的B值下，使系统不稳定的A值(阶跃信号的幅值)，并与用劳斯稳定判据计算的结果比较。 (With local parameter optimization method to design a model reference adaptive system, adjustable gain initial Kc (0) = 0.2, for a given value of r (t) for the unit step signal that r (t) = A × 1 ( t). Requirements: a continuous system discretization (sampling time of 0.1 preferred). 2 compiled and run the system computer program (Note B to adjust the value of the system to obtain better adaptive characteristics). 3 records ym, yp curve record kp × kc curve records generalized output error e curves. 4 parameter convergence, let Kp = 2 into the Kp = 1, re-observed Kp × Kc and e curves. B-5 to find value in determining the next, making the system unstable A value (step signal of amplitude), and using Routh stability criterion and the comparison of the results calculated.)

机器人定位与kalman滤波的学位论文与源程序(Robot localization and kalman filtering and source of dissertation)