FrequencyLowPass

《MATLAB简明教程》俺买的最新版的MATLAB教材，相当权威的，你绝对下不到更好的 了("Concise Guide to MATLAB," I bought the latest version of MATLAB materials, authoritative, you definitely less than the better)

基于知识的恒虚警检测——KB-CFAR检测器：包括对于无目标、仅有噪声的信号进行KB-CFAR检测的仿真，以及对于含目标、且在瑞利杂波背景下的KB算法仿真。一些程序主要是为了绘图，画出KB-CFAR检测过程中的信号波形以及检测门限对比图；而另一些程序是为了计算KB-CFAR检测过程中的检测概率和虚警概率。(KB-CFAR detectors: simulations of detection to signals with no target but noise only, as well as signals with target and the background of Rayleigh clutter. Some programs are aimed at giving pictures of the signals and detectiong threshold in the process of detection using KB-CFAR algorithm, while other programs are aimed at calculating the detecting rate and false alarm rate of KB-CFAR algorithm.)

matlab仿真教程，simulink模块讲解(matlab simulation tutorial)

Genetic Algorithm using matlab

利用A星算法进行二维路径规划，用MATLAB软件进行仿真(Two-dimensional path planning using A-star algorithm and simulation using MATLAB software)

说明：  Parzen窗法，由样本求概密估计，例为一维正态分布和双峰均匀分布，内附随机数生成的原理说明。( window method, by the sample density estimate for estimated Example for one-dimensional normal distribution and bimodal uniform distribution, random number generator containing a description of the principle.)

MAterial for different components on embedded system

this is a SDIF algorithm code for deinterleaving radar pulse

基于MATLAB的 NewtonRaphson的极坐标表示的潮流计算程序，希望对大家有帮助。(Based on MATLAB-NewtonRaphson express the polar coordinates of the flow calculation procedure, in the hope that everyone has to help.)

在这项工作中所使用的方法是基于一个由大卫阿诺德教程。 http://online.redwoods.cc.ca.us/instruct/darnold/diffeq/logistic/logistic.pdf 这将运行该Logistic.m带来了图形用户界面。 1。放弃在列的格式文本文件中的x值 2。放弃在山口格式文本文件中的y值 3。的阴谋初始 按钮将绘制的分布 4。 查找适合 按钮，会找到最适合 5。 重置 将删除的情节（虽然我想打扫所有的领域 -没有时间） 5。地下K，糖尿病在下列公式中的值 Ÿ 等于k/（1+进出口（- G *的（十型录））） 6。上证所给出了squred误差之间的拟合函数与实际数据的总和 7。消委会提供的相关合作关系的实际数据拟合功能和效率(The method used in this work is based on a tutorial by David Arnold. http://online.redwoods.cc.ca.us/instruct/darnold/diffeq/logistic/logistic.pdf RUN The Logistic.m this will bring up the GUI. 1. Give the x values on a text file in column format 2. Give the y values on a text file in col format 3. Plot Initial Button will plot the distribution 4. Find Fit button will find the best fit 5. Reset will remove the plot (Although I wanted to clean all the fields- did not have time) 5. K, G, Dm are the values in the following equation y = K./(1+exp(-G*(x-Dm))) 6. SSE gives the sum of squred error between the fitted function and the actual data 7. CC give the correlation co-efficient between the fitted function and actual data)