TenLecturesonWavelets

FastICA Code. Independent Component Analysis code for signal extraction

用自适应法做时延估计，然后根据时延估计确定声源的定位(Adaptive time delay estimation method used to do, and then determine the time delay estimation based on the positioning of the sound source)

录制自己的一段语音，时间控制在15秒到30秒左右；利用wavread函数对自己的语音进行采样，记住采样频率。 （1）画出原始语音信号的时域波形，而后以1秒为间隔，求出每秒数据的功率谱。 （2）根据语音信号特点，分别设计FIR及IIR滤波器，分别画出滤波器幅频和相频特性曲线。用设计的滤波器对信号滤波，画出滤波后时域波形。用sound函数回放语音信号。 （3）求出特征频段语音信号随时间变化的曲线（每间隔0.05秒求一次功率谱）。 (Record your own voice for some time (15 seconds to 30 seconds) use wavread function of the voice samples, remember the sampling frequency. (1) Draw the original speech signal in time domain waveform, and then to 1 second intervals, the data obtained power spectrum per second. (2) According to the voice signal characteristics, FIR and IIR filters were designed, namely to draw the amplitude and phase frequency characteristic curve. With the design of the filters on the signal filtering, to draw the filtered time-domain waveform. Playback with sound function of the speech signal. (3) Find the characteristic band speech signal curve over time (0.05 seconds intervals seeking a power spectrum.))

adaptive control mrac

documentation of the varioref latex package

基于matlabGUI 的图形化界面，展示了snake能量边缘算法检测，并通过调节参数查看算法效果(MatlabGUI-based graphical interface that shows the snake energy edge detection algorithm, and the algorithm by adjusting the parameters to see the effect of)

说明：  利用人工与算法、蝙蝠算法、遗传算法、粒子群算法等进行最优值的求解(Using artificial and algorithm, bat algorithm, genetic algorithm, particle swarm optimization algorithm to solve the optimal value)

matlab实现最大熵法图像分割程序源代码(Matlab maximum entropy image segmentation method source code)

一款利用matlab编写的射线追踪程序，易改易用。(The installation of TTBOX is relatively simple. All you have to do is to create some directories and tell MatLab, where TTBOX is. if it does not already exist, create a directory matlab within your home directory. Copy the TTBOX directory into the matlab directory if it does not already exist, create a file startup.m within the matlab directory Insert the following lines into startup.m: basepath= This should be the path to your home directory! addpath([basepath filesep matlab filesep ttbox ],1) addpath([basepath filesep matlab filesep ttbox filesep support ],1) execute startup within the MatLab command window. MatLab is now ready to execute TTBOX routines. The startup-script will be executed automatically upon start of MatLab. In order to read the online documentation, you have to browse to the doc directory and open the ttbox/doc/ttbox.html file with your web browser (it is recommended to set a bookma)

Lung Cancer Detection in matlab