Smith

说明：  《信号与系统》奥本海姆著，信号分析处理的经典教材，学小波分析必看的基础书(&quot Signals and Systems&quot Oppenheim a, signal analysis and processing of the classic textbooks, school books based on wavelet analysis a must-see)

Assignment 1 given to me by my lecturer

matlab code for stlwrite - Write binary or ascii STL file

simulation 4psk on fading channel

非常有用的卫星轨道参数计算模块,很方便进行轨道特性分析。(This is a very useful toolbox for satellite s trajectory parameter computation )

云模型matlab源代码,下载后可以直接使用(Cloud model can be directly used in the source code)

本程序是用自适应遗传算法进行图像增强，其思想来自《计算机学报》发表的论文。(This program is self-adaptive genetic algorithm image enhancement, their thoughts from the " Journal of Computers," published papers.)

matlab partial code for reference purpose

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)

Poer spectral density of BPSK, QPSK and 16-QAM