QPSO

独立分量分析的开关算法代码 ，内有pdf格式说明文挡 希望有用(independent component analysis algorithm code switch, which shows a pdf format text block useful hope)

微分方程求解，利用matlab软件，解决微分方程领域各种问题(Solving differential equations using matlab software, field problems to solve differential equations)

是粗糙集中很不错的代码。。。。这里面还含有粗糙集的论文 愿意与大家共享(Rough set is very good code. . . . There also contains a rough set of papers are willing to share with you)

比较四分量信号的不同时频分布结果,小波分析。(Compare the results of time-frequency distribution of the four components of the signal)

这本书，是通过一些实际的例子来让你学习MATLAB。(This book, through some actual examples to learn MATLAB.)

【谷速软件】红外与可见光图像自适应融合源代码 ( 在学习过程中作为参考使用)

位置指令为幅值为1.0的阶跃信号，r（k）=1.0。网络结构为1-4-1，高斯函数的参数值取Cj=[-2 -1 1 2]T ，B=[0.5 0.5 0.5 0.5]T 。 网络权值学习参数为η=0.30，α=0.05 。PID控制各参数的初RBF网络控制，被控对象为G（s）= 取采样时间为1ms，采用Z变换进行离散化，离散化后的被控对象为 y(k)=-den(2)*y（k-1）-den(3)*y(k-2)+num(2)*u(k-1)+num(3)*u(k-2) 始值为，kp=20， kd=0.3， ki=0.1。 (Position command for the step signal amplitude of 1.0, r (k) = 1.0. The network structure is 1-4-1, the Gaussian function parameters taken Cj = [-2-1 1 2] T, B = [0.5 0.5 0.5 0.5] T. Weight learning parameter η = 0.30, α = 0.05. PID control parameters at the beginning of each RBF network control, the controlled object is G (s) = take the sampling time is 1ms, using the Z transform discrete, discretized controlled object is y (k) =-den (2)* y (k-1)-den (3)* y (k-2)+num (2)* u (k-1)+num (3)* u (k-2) initial value, kp = 20, kd = 0.3, ki = 0.1.)

skewnee correction for 2d image ya

计算每个IMF分量及最后一个剩余分量residual与原始信号的相关性;计算各IMF的方差贡献率;绘制FFT频谱(The correlation between each IMF component and the last residual component residual and the original signal is calculated; the variance contribution rate of each IMF is calculated; and the FFT spectrum is drawn.)

A speech signal filterbank, using melscale frequency and framebanking.( 1. For speech signal can be represented as a discrete sequence of frames (or feature vectors) that can be used as the input to a speech recogniser. Important ideas and techniques that are used in the assignment are the design of a (Mel frequency scale) audio filterbank, , windowing of a continuous audio signal, spectrum analysis of the signal, filtering as multiplication in the frequency domain, the visual representation of a speech signal as a spectrogram, appreciation of the acoustic variability in real speech utterances. 2. To gain a deeper knowledge of the application of MATLAB programming to audio signal processing. 3. To gain practice in the art of writing a formal report: structure, content, style, use of diagrams, presentation etc. etc. )