Matlab-for-Neuroscientists

视频的编码和解码过程的简单仿真，输入图像是一幅RGB图像，对其的编码过程都尽量模拟模拟视频的方式(Video encoding and decoding process of a simple simulation, the input image is a RGB image, the encoding of their simulation process as far as possible the way analog video)

Advances in data collection and storage capabilities during the past decades have led to an information overload in most sciences. Researchers working in domains as diverse as engineering, astronomy, biology, remote sensing, economics, and consumer transactions, face larger and larger observations and simulations on a daily basis. Such datasets, in contrast with smaller, more traditional datasets that have been studied extensively in the past, present new challenges in data analysis. Traditional statistical methods break down partly because of the increase in the number of observations, but mostly because of the increase in the number of variables associated with each observation. The dimension of the data is the number of variables that are measured on each observation.

一个用在simlink 中用 dsp builder建立的FIR滤波器，每个波形都有波形显示，是学习DSP builder和FIR滤波器好资料。(One used in the FIR filter using dsp builder simlink established, each waveform has a waveform display, learning DSP builder and FIR filter good information.)

关于基于训练序列的OFDM系统全面的同步算法仿真,包括定时同步,采样同步,载波同步,代码逐点执行,顶层文件为PLC_sync_test.m(Training sequence based on the OFDM system for synchronization algorithm simulation, including the timing synchronization, sampling synchronization, carrier synchronization, code-by-point implementation, the top-level document PLC_sync_test.m)

BP神经网络模型，用于根据反馈信息，调整，以达到最优值(BP neural network model for feedback adjustments to achieve the optimal value)

课件详细的讲解了关于图像处理和分析的相关知识(Detailed explanation of courseware on image processing and analysis knowledge)

基于点扩散函数的多聚焦图像融合算法(Point spread function based on multi-focus image fusion)

he files in this package comprise the Matlab implementation of a foreground segmentation algorithm based upon graph cuts, described in: Better Foreground Segmentation Through Graph Cuts, N. Howe & A. Deschamps. Tech report, http://arxiv.org/abs/cs.CV/0401017. The file extractForeground.m contains a sample function that will perform a complete foreground segmentation for static camera video. It uses a number of parameters, which are described in the documentation. An attempt was made to choose sensible default values, but they may need to be adjusted for some videos. More generally, the implementation in extractForeground.m is only a suggestion of how the graph-based segmentation might be used. The same approach can be applied with other (perhaps time-adaptive) background models. The key step is at line 113 of the code, once the deviation array has been created. The graph-cut segmentation can be applied similarly to a deviation matrix computed in any other way.

Signal processing algorithms to extract heart beats in recordings of heart muscle activity

说明：  用SIMULINK编写的二自由度车建模，一为数据文件，一为建模文件(SIMULINK prepared with the two degree of freedom model cars, as a data file, a document for Modeling)