DSPMain

这是介绍基于蚁群优化算法的碎纸拼接的文章(This is to introduce ant colony optimization algorithm shredding stitching articles)

近场声源定位TDOA的MATLAB仿真，采用传统的相关算法CC和广义相关算法中的相位转换算法GCC_PHAT(Sound localization of MATLAB simulation, using the traditional algorithms of CC and phase transformation algorithm of generalized correlation algorithm GCC PHAT)

nice document about the fast manipulation of multi-dimensional arrays in matlab,with some examples to avoid loops and using indices

说明：  利用matlab对平平腔中自在现模的进行了模拟(Using matlab to the flat itself is in the mold cavity has been simulated)

基于预测控制的永磁同步电机直接转矩控制，利用matlab/simulink平台建立了永磁同步电机直接转矩控制的仿真模型(Based on predictive control of permanent magnet synchronous motor direct torque control of permanent magnet synchronous motor was established based on matlab/simulink platform simulation model of direct torque control.)

Kalman Filtering Theory and Practice, Using MATLAB

This script will setup the nonlinear simulation (UAV_NL.mdl) and call trim and linearization routines. Select the desired aircraft here in this script, via the "UAV_config()" function call.

OPENCART V1.56 中文使用说明书，主是要讲怎么配置商城。(OPENCART V1.56 Chinese instructions for use, the main is to tell how to configure the mall.)

Source separation problems in digital signal processing are those which are used to separate useful signal a mix of signals of interest, other signals and noise. The typical example of a source separation problem is the cocktail party problem, where many number of peoples are talking simultaneously in a room and a listener is trying to follow one of the discussions. The human brain can separate the voices of different people (source separation) using neurons in the auditory region. But source separation using digital signals is difficult task with the available techniques. Several approaches have been proposed for solving this issue but most of the techniques are still in development stages. Some of the successfully tested approaches are principal components analysis (PCA) and Independent components analysis (ICA). Both the approaches work well when there are no delays or echoes present

eeglab中使用ICA算法后的自动伪迹识别插件adjust，可以自动识别独立成分的伪迹成分，可用于去除眼电、心电等伪迹，解压后安装在eeglab/plugins文件夹中即可在eeglab-tools中调用(independent component analysis algorithm)