SIMPSON1_3_matlabfa

adaptive control matlab m file

初学matlab的教程，比较全面，比较实用，此部分为第二部分。(Matlab beginner tutorial, more comprehensive, more practical, this part of the second part.)

计算电磁学，E文，适用于电磁场，微波，射频等专业，简单易懂且实用，有MATLAB例子，不容错过(Computational electromagnetics, applies to electromagnetic fields, microwave, radio frequency, and other professional, easy to understand and practical, MATLAB examples, not to be missed)

学习matlab与DSP之间的接口的好资料，大家一起学习吧(Learning matlab and DSP interface between good information and we can work together to learn it)

NLMS算法的仿真程序,初级入门的matlab仿真程序(NLMS algorithm simulation program, the initial entry of matlab simulation program)

IIR直接型系统结构转换为级联型系统结构(IIR direct-type system structure into a cascade system structure)

用于将RGB彩色图转化为灰度图的matlab代码！(Gray color map of the matlab code!)

用falman滤波进行目标的识别和跟踪，此外还使用了矩不变性(Falman filtering target identification and tracking, in addition to using the Moment invariance)

说明：  遗传算法，一个不错的程序，可以试试看，改进了一点点，大学共同探讨 了(Genetic algorithm (ga), a good program, can try to improve a little bit, the university is discussed )

Magnetic resonance (MR) images can be used to detect lesions in the brains of multiple sclerosis (MS) patients and is essential for diagnosing the disease and monitoring its progression. An automatic method is presented for segmentation of MS lesions in multispectral MR images. Firstly a PD-w image is subtracted its corresponding T1-w image to get an image in which the cerebral spinal fluid (CSF) is enhanced. Then based on kernel fuzzy c-means (KFCM) algorithm, the enhanced image and the corresponding T2-w image are segmented respectively to extract the CSF region and the CSF combining MS lesions region. A raw MS lesions image is obtained by subtracting the CSF region CSF combining MS region. By applying median filter and thresholding to the raw image, the MS lesions are detected finally. Results are quantitatively uated on BrainWeb images using Dice similarity coefficient (DSC). Finally, the potential of the method as well as its limitations are discussed.