MATLAB-Neural-network-analysis

The problem of enhancing speech degraded by uncorrelated additive noise, when only the noisy speech is available, has been widely studied in the past and it is still an active field of research

High pass and low pass filters with matlab by using bode plot method. Showing very important thing is that bode plot does not give any information about transient response.

说明：  three level dtc induction machine

说明：  并网逆变器下垂控制特性仿真，能正常仿真，波形控制输出有振荡，共学习参考使用。(droop control:The network-connected inverter sagging control characteristics simulation, can be normal simulation, waveform control output oscillation, a total learning reference use.)

说明：  线性调频信号的雷达仿真三个目标距离测试Range Testing of Three Targets in Radar Simulation of LFM Signal(Range Testing of Three Targets in Radar Simulation of LFM Signal)

matlab basic book ,介绍一些关于matlab 的知识以及其用法，对于初学者强烈推荐，可作为入门教程，有比较多的例子(matlab basic book, some knowledge on matlab and its usage, strongly recommended for beginners and can be used as entry-course, there are more examples of)

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)

使用高斯白噪声和正弦信号模拟产生肌电信号(Gaussian white noise and sine generated EMG signal simulation)

采用matlab语言对扩散微分方程进行了求解的M文件(The code is diffusion pde equation in matlab language)

波束形成中mvdr和music算法精确性对比分析，可对两个声源进行识别(Mvdr and music beamforming algorithm accuracy comparative analysis of the two sound sources can be identified)