matlab-100-examples

中值滤波和它的改进 自己实现的 可能比较粗略 matlab2013运行通过(Median filter and it is possible to achieve improved their sketchy matlab2013 run through)

matlab里面典型的图论工具箱使用例子.对于一般的同学学习,是个较好的入门程序.(matlab toolbox inside the typical examples of the use of graph theory. For the average student learning, is a good entry procedures.)

用matlab实现了基于而阶累积量的music算法测角,非常基本,注释详细,欢迎使用(matlab music )

image segmentation using matlab

hspice toolbox interface between hspice and matlab

Sanjit K.Mitra著《数字信号处理——基于计算机的方法》第三版配套光盘中的MATLAB示例程序(Sanjit K.Mitra a digital signal processing- a computer-based method, the third edition of the companion CD in the sample program MATLAB)

含GUI界面的数独游戏，具有多种帮助提示功能，以提高解题能力。(A GUI for helping you to solve sudoku puzzles onscreen)

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)

DBPSK transreceiver design model using simulink

该算法利用BP神经网络描述了一个同心圆的分类算法。特点是可以任意定义多个隐层及隐层内的神经元数目。(the algorithm discribed a category of samecircle.with it you can define any number of buried layer and never cell number of each buried layer.)