shiyan

利用matlab对随机过程课程的仿真 1、利用matlab绘制随机过程的谱密度G_x (ω)=2αβ/(β^2+ω^2 ) (α、β为正数)的图像。 2、绘制白噪声的功率谱密度函数G_x (ω)=N/2和自相关函数R_N (τ)=N/2 δ(τ)的图像。 3、分析低通白噪声和带通白噪声的功率谱密度函数和自相关函数的性质并举例同时绘制其图像。 (1, drawn using a random process matlab spectral density G_x (ω) = 2αβ/(β ^ 2+ ω ^ 2) (α, β positive) image. 2 for the white noise power spectral density function G_x (ω) = N/2 and the autocorrelation function R_N (τ) = N/2 δ (τ) of the image. 3, the analysis of low-pass white noise and band-pass white noise power spectral density function and autocorrelation function of the nature and the examples at the same time to draw its graphics.)

干涉图像光谱复原matlab仿真,主要通过设置虚拟光源光谱、对波真面分束空间干涉模型设定以及光谱复原等组成。(Resctruction the spectrum from the image of interference )

说明：  BP神经网络，matlab程序编写，有原始数据，可用于遥感图像分类，并且对遥感图像的土地利用类型进行预测。(BP neural network, matlab programming, with original data, can be used for remote sensing image classification, and remote sensing image land use type prediction.)

输入一副图像，检测图像的RGB，并输出其值的矩阵，将符合公式R>Rt，R>G>B,S>=(255-R)*S/R,等的图像点标记出来，并输出图像(A pair of input images, the image detecting RGB, and outputs the value of the matrix, would be consistent with the formula R> Rt, R> G> B, S> = (255-R)* S/R, and other image point marked, and output image)

电机dqo系统放着程序，大家多交流............(Motor dqo system stood process, everyone was sharing ............)

上传的为粒子群优化算法的仿真程序，MATLAB编程。(Particle Swarm optimization)

txt格式心电信号的载入及滤波，滤波方法有巴特沃斯低通和小波分析(txt format to load and ECG filtering, Butterworth filtering methods and wavelet analysis of the low-pass)

在matI ab中模拟c中链表，利用复数运算， 联系具体字符和概率，每次找到最小概率的 两个字符对应的蝙号，依次记录下来，最后 根据奇偶码的不同实现Huffman蝙码。本算法 新颖独特， 易于理解、蝙程。(Simulate in matI ab c in the list, using complex operation, contact the specific character and the probability to find the minimum probability for each of the two characters corresponding to bat number, followed by record, last achieved according to the different parity code Huffman bat code. This algorithm is novel and unique, easy to understand, bat-way.)

用于三分类的bp算法matlab程序 下面是一个两概念（一个三角形和一个矩形）学习的例子，是一个典型的多分类例子 分类结果的正确率可通过训练网络进一步提高 (for three classification algorithm Matlab procedures bp below is a two concepts (a triangle and a Moment fractal) learning example is a typical example of multi-classification results of the correct classification rate can be further enhanced training network)

matlab仿真精华，关于三相异步电机调速的案例，很有用(the matlab simulation essence, about the case of the three-phase induction motor, useful)