Merge-putFilesToOneDir

说明：  表面肌电信号数字传感器的设计。表面肌电（suRFace electromyography, sEMG）信号是神经肌肉系统在进行随意性和非随意性活动时的生物电变化经表面电极引导、放大、显示和记录所获得的一维电压时间序列信号，其振幅约为0-5000μV，频率0-1000Hz，信号形态具有较强的随机性和不稳定性。与传统的针式肌电图相比，sEMG的空间分辨率相对较低，但是探测空间较大，重复性较好，对于体育科学研究、康复医学临床和基础研究等具有重要的学术价值和应用意义[1]。(Surface EMG digital sensor design)

利用支持向量机的最优算法,来分割图像,可以得到有效地细胞分离图片(Using the optimal algorithm of support vector machine to segment the image, we can get the cell separated image effectively.)

生命系统建模——血液血环系统的建模，能够对多种心血管疾病情形进行模拟。(Life System Modeling- Modeling blood blood ring system, it is possible to simulate a variety of cardiovascular disease situations.)

电力黑启动综合程序,用于大面积断电以后,快速恢复电力,含多个子程序(Power black-start synthesis program, used for power recovery after a large area power failure, including a number of subroutines)

一个可以识别金钱豹、老虎、长颈鹿、斑马、鸵鸟、企鹅、信天翁等七种动物的简单专家系统(it is a simple expert system that can identify seven kinds of animals such as leopard,tiger,giraffe,zebra,ostrich, penguin and albatross)

A small programmer written by VC to show the earth, can move with the mouse

该工具箱主要功能：显示心电信号，分析心电信号中的outlier(ECG signal display，ECG signal analysis)

MATLAB心电图自动诊断程序。围绕心电信号预处理、心电波形检侧与定位、心电特征提取与分析三个方面。研究MIT数据库中的心电信号，针对心电信号中存在的工频干扰、基线漂移、肌电干扰等各种噪声,设计出了高通、低通、带阻、平滑效果滤波器来对心电信号进行预处理，对处理后的信号采用连续小波变化进行特征点的定位及瞬时心率的计算，最后通过分析给出诊断结果。(MATLAB ECG automatic diagnosis program. Around the ECG signal preprocessing, ECG waveform detection and location, ECG feature extraction and analysis of three aspects, the study of MIT in the ECG signal. According to the frequency interference, baseline drift in the presence of ECG, EMG interference and other noise, design a high pass, low pass, band stop filter, smoothing effect of pretreatment of the ECG signal, the calculation of the processed signal using continuous wavelet transform to locate feature points and instantaneous heart rate, finally the diagnosis results.)

筛选的几篇脑电节律提取的文章，可以用于其它信号处理~ 【基于改进小波变换的EEG分析】【基于小波变换的动态脑电节律提取】【脑电信号的特征节律信号提取】【a、β、δ、θ和40Hz波实时检测器】(Screening of several EEG extracted article, can be used for other signal processing ~ 【EEG based on improved wavelet analysis】 【based on wavelet transform extracts】 【dynamic EEG characteristics of EEG signal extraction】 【a rhythm , β, δ, θ, and real-time 40Hz wave detector】)

孟德尔隐马尔科夫的源程序，对于孟德尔隐马尔科夫的研究者有帮助