154a_chmodel_v9

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)

介绍matplotlib编程的一本电子书籍，讲解生动，由浅入深。(An electronic book that introduces matplotlib programming. )

PWM整流器仿真，能够控制功因数，希望对大家有所帮助(PWM Rectifier simulation, able to control the power factor, we hope to help)

基于matlab对灰度图像的二值化自适应阈值的算法(Gray image binarization adaptive algorithm)

本文主要利用matlab编程工具对直接序列扩频通信的捕获过程进行仿真。仿真主要基于滑动相关法的有关理论,先讨论扩频仿真中起着重要作用的m序列的生成问题,尔后讨论调制信号的产生,然后在信号的捕获中分步讨论,先对捕获的流程进行简单的仿真,再依次加入噪声和多普勒频移后进行捕获仿真(In this paper, using matlab programming tools for direct sequence spread spectrum communication capture process simulation. Simulation of the sliding correlation method is based on the theory, first discuss the simulation plays an important role in spreading the m sequence generation problem, the modulation signal generation and later discussed, and the signal captured by stepping discussion processes the captured first simple simulation, and then followed by adding noise and Doppler frequency shift after the capture simulation)

3D PLOT USING MATLAB IN PSCAD WARNING * This case only works if you use the Compaq/Intel Fortran Compiler. A T_D_PLOT component. It provides the interface to a MATLAB function t_d_plot . It is a user-defined function and the m-file T_D_plot.m contains its definition. This component plots a 3-dimensional curve. Input: X, Y and Z values of the point to be plot Output: a dummy output of value zero Parameters of T_D_PLOT component.

森林火灾仿真，元胞自动机，可视化设计，非常经典(Forest fire simulation, cellular automata, visual design, very classic)

RDP-距离域分段滤波-预处理 (RDP- distance domain segment filtering preprocessing)

A simple m-file to compute the experiemntal BER of coded BPSK(A simple m-file to compute the experiemnta l coded BER of BPSK)

for communication eng matlab