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MATLAB PROGRAM TO CHECK CONTROLLABILITY AND OBSERVABILITY

matlab互相关函数，可用于地震数据处理。(auto correlation of the seismic data)

在复杂背景下面，如何识别交通标志。。。。。。(Traffic sign recognition is a difficult task if we aim at detecting and recognizing signs in images captured from unfavorable environments.)

alphabet recognization, a simplified version only to detect few numerical pronunciations

机动目标一阶加速度的频率普分析，以及多普勒展宽，相干积累。以70km，径向速度700m，加速度20m/s^2目标为例(An acceleration of maneuvering target frequency bands Pu analysis, and Doppler broadening, coherent accumulation. To 70km, the radial velocity 700m, acceleration 20m/s ^ 2 goals, for example)

说明：   改进的牛顿法求解： 方程的构造方法:给出[0,1]区间上的随机数(服从均匀分布)作为方程的根p*. 设你的班级数为a3,学号的后两位数分别为a2与a1,从而得到你的三次方程 例如:你的31班的12号,则你的方程是21x3+60x2+2x+a0=0的形式. 方程中的系数a0由你得到的根p*来确定. (improve Newton's method : Construction of the equation : given interval [0,1] on the random number (subject to uniform distribution) as the root equation p*. set up your classes at a3, after learning of the double-digit for a1 and a2, so you get the three equations for example : Your 31 classes on the 12th, then your equation is 21x3 60x2 2x a0 = 0 forms. the equation coefficients a0 you get from the root of p* to determine.)

用simulic编写了生成信号 很详细很好用呢(singal simulic)

奇异谱分析是近年来兴起的一种研究非线性时间序列数据的强大的方法。它根据所观测到的时间序列构造出轨迹矩阵，并对轨迹矩阵进行分解、重构，从而提取出代表原时间序列不同成分的信号，如长期趋势信号、周期信号、噪声信号等，从而对时间序列的结构进行分析，并可进一步预测。(Singular spectrum analysis is a powerful method to study nonlinear time series data in recent years. According to the time sequence structure of the observed path matrix, and the trajectory matrix is decomposed and reconstructed, thus extracting the signal representative of the original time series of different components, such as the long term trend signal and periodic signal and noise signal, through analyzing the structure of the time series, and further predict.)

Autocorrelation speech signal for matlab. Computes the f0 frequency.

用于求解半线性椭圆问题的瀑布型多网格算法，可以求解到很高的精度，(Used to solve semi-linear elliptic problem Falls Multi-grid method, you can solve to a high precision,)