Walsh---Hadamard-transform

基于MATLAB的信号表示及运算，实现信号的反转、平移、展缩、相加和相乘。(MATLAB-based signal representation and computation, to achieve signal inversion, translation, exhibition shrinking, adding and multiplying.)

该程序基于matlab，可以对输入的一个ECG信号图像进行处理，方便进一步分析。(Based on matlab, the program can enter an ECG signal image processing to facilitate further analysis.)

连续潮流计算 对不同网络进行电压稳定极限分析(OPF calculation)

matlab code for engineer

Contrast Limited AHE (CLAHE) differs from ordinary adaptive histogram equalization in its contrast limiting. This feature can also be applied to global histogram equalization, giving rise to contrast limited histogram equalization (CLHE). In the case of CLAHE, the contrast limiting procedure has to be applied for each neighbourhood from which a transformation function is derived.

matlab reference manual

matlab simulink matlab simulink (matlab simulink matlab simulink )

《MATLAB数字信号处理》一书源码， 王彬主编，机械工业出版社。压缩文件包括书的ppt文件，和相关的例子源码("MATLAB digital signal processing," source code book, edited by Wang Bin, Machinery Industry Press. Zip file includes the book ppt files, source code and related examples)

thesis program of the inverter

The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order (The main features of the considered identification problem are that there is no an a priori separation of the variables into inputs and outputs and the approximation criterion, called misfit, does not depend on the model representation. The misfit is defined as the minimum of the l2-norm between the given time series and a time series that is consistent with the approximate model. The misfit is equal to zero if and only if the model is exact and the smaller the misfit is (by definition) the more accurate the model is. The considered model class consists of all linear time-invariant systems of bounded complexity and the complexity is specified by the number of inputs and the smallest number of lags in a difference equation representation. We present a Matlab function for approximate identification based on misfit minimization. Although the problem formulation is representation independent, we use input/state/output representations of the system in order)